Developing a reproducible approach for generating FCTs & NCTs
Technical webinar on the extension of the global food composition table for fisheries. November, 2022
Agenda (1)
Introduction
Objectives
Development of a framework for compiling NCTs. The Extended Fisheries Global NCT (2022) as case study
- Background and starting point for the NCT
- Harmonising Food Composition Tables and Databases
- Visualisation for nutrient evaluation and missing values identification
Agenda (2)
The Extended Fisheries Global NCT (2022)
- Food composition data for fishery products: Overview
- Visualisation for decision making (missing values and outliers)
- How scripted approach allow for fast update and re-use of the FCT for new purposes
- How collaborative coding and GitHub increases efficiency and transparency of the approach
Conclusions & Recommendation for the future
- What has been completed – what needs to be further advanced?
- The need of better nutrition data for decision-making
- New data skills and statistical approach for better food and nutrition data.
Q&A: Discussion & Next Steps
Introduction
Meet the team!
- Lucia Segovia de la Revilla
- Thomas Codd
- Liberty Mlambo
- Louise Ander
School of Biosciences
Objective
Applying MAPS framework:
to expand the Fisheries Global Nutrient Conversion Table (NCT)
The Fisheries Global Nutrient Conversion Table
The Fisheries Global Nutrient Conversion Table
The Fisheries Global NCT provided information on:
- 21 Food components.
- 95 ICS SUA Fisheries (and Aquatic Products) Categories.
- 11 Food composition tables and databases (FCTs).
The Fisheries Global Nutrient Conversion Table
The Fisheries Global NCT provided information on:
- 21 Food components + evaluate 10 fish-relevant food components.1
- 95 ICS SUA Fisheries (and Aquatic Products) Categories.
- 11 Food composition tables and databases (FCTs).
Development of the framework for compiling NCTs
Why the framework was needed?
- FCTs are available in multiple data formats.
- Data harmonisation requires effort, expertise, and time.
- Increasing the standardisation of the FCTs would…
... Lower cost of updating & generating new NCTs.
... Increase reproducibility of NCTs and their survey outputs.
... Increase re-usability & dissemination of FCTs.
Overview of the NCT framework
Steps 1 & 2: Data Sources & Importing
Downloading and storing original 11 FCTs 1 + Norwegian FCT (2021).
FCTs were imported into R(Studio) & independent scripts were generated for each FCT.
All the data operations (from Step 2 to Step 6) were done in R(Studio).
Step 3: Data cleaning and standardisation of FCTs
Food component names/ description standardisation using Tagnames1. For example…
“Vitamin B12” -> VITB12
“Vitamin A” -> VITA or VITA_RAE?
“Vitamin B6” -> VITB6A or VITB6C or VITB6-?
Step 3: Data cleaning and standardisation of FCTs
Food (fish) name/ description standardisation:
*Aquatic Sciences and Fisheries Information System
Step 3: Food name/ description standardisation
Fisheries categories matching in Norwegian FCT (2021).
Scientific names were used to allocate the ‘International Standard Statistical Classification for Aquatic Animals and Plants’ (ISSCAAP) codes.
ISSCAAP codes and text pattern (food description) to allocate ICS SUA Fisheries codes.
Review and final allocation of unidentified fish items were performed.
Step 4a: Data harmonisation and compilation of FCTs
Character values standardisation. For example, trace (“tr”) or below detection limit (“<LOD”) to zero (0) or removing special characters (“[]”, “()”, “*”).
Unit of measure standardisation. For example from mg/100g to g/100g.1
Harmonising Food Composition Tables and Databases. From 12 individual FCTs to a compiled FCT data library.
Step 4b: Variable recalculation and missing values
Other data transformation were performed in the harmonised data library.
Re-calculation of food components. For example, Energy, Carbohydrates by difference or Vitamin A (RAE).
Back-calculation from other components. For example, Niacin, preformed was back-calculated from Niacin, equivalents and Tryptophan.
Combining food components. For example, Vitamin B6 included: Vitamin B6 determined by analysis, determined by calculation and by unknown method.
Data imputation: For example, if a ICS SUA fishery category did not provided data for one nutrient.
Functions: Re-calculation
Functions were developed to re-calculate:
SOP_std_creator() - Sum of Proximate
ENERCKcal_standardised() - Energy (kcal)
CHOAVLDFg_std_creator() - Carbohydrates by difference
VITA_RAEmcg_std_creator() - Vitamin A (REA)
CARTBEQmcg_std_creator() - Beta-Carotene Eq.
Functions: Energy
Functions: Energy
Functions: Re-calculation
Functions were developed to re-calculate:
SOP_std_creator() - Sum of Proximate
ENERCKcal_standardised() - Energy (kcal)
CHOAVLDFg_std_creator() - Carbohydrates by difference
VITA_RAEmcg_std_creator() - Vitamin A (REA)
CARTBEQmcg_std_creator() - Beta-Carotene Eq.
Functions: Beta-Carotene Equivalents
CARTBEQmcg_std_creator <- function(dataset) {
# Check presence of required columns
columns <- c("CARTBmcg", "CARTAmcg", "CRYPXBmcg")
check_columns(dataset = dataset, columns = columns)
# Try the calculation
tryCatch(
dataset %>%
as_tibble() %>%
mutate_at(.vars = columns, .funs = as.numeric) %>%
# ! Create a temp row with the count of NAs in the required columns
mutate(temp = rowSums(is.na(
dataset %>%
select(all_of(columns))
))) %>%
rowwise() %>%
# ! Replace comment NAs with blank so that we can concatenate comments well.
mutate(comment = ifelse(is.na(comment), "", comment)) %>%
# ! If all inputs to the CARTBEQmcg_std calculation are NA return NA
# ! Else perform calculation ommiting NAs
mutate(CARTBEQmcg_std = ifelse(
temp == length(columns),
NA,
sum(1 * CARTBmcg, 0.5 * CARTAmcg, 0.5 * CRYPXBmcg, na.rm = TRUE)
))
}Functions: Beta-Carotene Equivalents
CARTBEQmcg_std_creator <- function(dataset) {
# Check presence of required columns
columns <- c("CARTBmcg", "CARTAmcg", "CRYPXBmcg")
check_columns(dataset = dataset, columns = columns)
# Try the calculation
tryCatch(
dataset %>%
as_tibble() %>%
mutate_at(.vars = columns, .funs = as.numeric) %>%
# ! Create a temp row with the count of NAs in the required columns
mutate(temp = rowSums(is.na(
dataset %>%
select(all_of(columns))
))) %>%
rowwise() %>%
# ! Replace comment NAs with blank so that we can concatenate comments well.
mutate(comment = ifelse(is.na(comment), "", comment)) %>%
# ! If all inputs to the CARTBEQmcg_std calculation are NA return NA
# ! Else perform calculation ommiting NAs
mutate(CARTBEQmcg_std = ifelse(
temp == length(columns),
NA,
sum(1 * CARTBmcg, 0.5 * CARTAmcg, 0.5 * CRYPXBmcg, na.rm = TRUE)
)) %>%
# ! Use the same logic as above for comment appendage.
mutate(comment = ifelse(
temp == length(columns),
comment,
paste0(
comment,
" | CARTBEQmcg_std calculated from CARTBmcg, CARTAmcg and CRYPXBmcg"
)
)) %>%
# ! Check which components of the calculation were used. If only CARTB was used. Append the comment to reflect that.
mutate(comment = ifelse(
(
temp != length(columns) &
!is.na(CARTBmcg) &
is.na(CARTAmcg) & is.na(CRYPXBmcg)
),
paste0(comment, " but only CARTB was used"),
comment
)) %>%
# ! remove the temp column
select(-temp) %>%
ungroup(),
error = function(e) {
print("Error : Required columns not found i.e :")
print(columns)
print("The CARTBEQmcg_std will not be calculated")
}
)
}
Functions: Back-calculation
Ash by difference (g/100g) - scripted
Beta-carotene equivalents (mcg/100g) -
CARTBEQmcg_std_back_calculator_VITA_RAEmcg()Retinol (mcg/100g) -
RETOLmcg_Recalculator()Niacin (mcg/100g) -
nia_conversion_creator()
Back-calculation: Ash by difference
Carbohydrates available by difference (g/100g) = 100 - (water + protein + fat + ash + alcohol + dietary fibre)
Ash by difference (g/100g) = 100 - (water + protein + fat + available carbohydrate + alcohol + dietary fibre)
Combination of variables
- Thiamin -
THIAmg_standardised - Vitamin B6 -
VITB6_mg_standardised - Fat -
FAT_g_standardised
#This function combine all the Tagnames for FAT_g_standardised
for(i in 1:nrow(fao_fish_fct)){
print(i)
if (!is.na(fao_fish_fct$FATg[i])) {
print(!is.na(fao_fish_fct$FATg[i]))
fao_fish_fct$FAT_g_standardised[i] <- fao_fish_fct$FATg[i]
}
if (is.na(fao_fish_fct$FATg[i])) {
fao_fish_fct$FAT_g_standardised[i] <- fao_fish_fct$FAT_g[i]
}
if (is.na(fao_fish_fct$FATg[i]) & is.na(fao_fish_fct$FAT_g[i])) {
fao_fish_fct$FAT_g_standardised[i] <- fao_fish_fct$FATCEg[i]
}
if (is.na(fao_fish_fct$FATg[i]) & is.na(fao_fish_fct$FAT_g[i]) &
is.na(fao_fish_fct$FATCEg[i])) {
fao_fish_fct$FAT_g_standardised[i] <- NA
}
print(fao_fish_fct$FAT_g_standardised[i])
}[1] 1
[1] TRUE
[1] "1.2"
[1] 2
[1] TRUE
[1] "0.7"
[1] 3
[1] "2.9"
[1] 4
[1] TRUE
[1] "3.064425770308123"
[1] 5
[1] TRUE
[1] "3.064425770308123"
[1] 6
[1] TRUE
[1] "3.5220588235294117"
[1] 7
[1] TRUE
[1] "3.5220588235294117"
[1] 8
[1] TRUE
[1] "3.8588235294117648"
[1] 9
[1] TRUE
[1] "3.8588235294117648"
[1] 10
[1] TRUE
[1] "1.411764705882353"
[1] 11
[1] TRUE
[1] "1.411764705882353"
[1] 12
[1] TRUE
[1] "1.6102941176470587"
[1] 13
[1] TRUE
[1] "1.6102941176470587"
[1] 14
[1] TRUE
[1] "1.5176470588235291"
[1] 15
[1] TRUE
[1] "3.1960784313725488"
[1] 16
[1] TRUE
[1] "3.1960784313725488"
[1] 17
[1] TRUE
[1] "2.0392156862745092"
[1] 18
[1] TRUE
[1] "2.0392156862745092"
[1] 19
[1] TRUE
[1] "2.1604278074866308"
[1] 20
[1] TRUE
[1] "2.1604278074866308"
[1] 21
[1] TRUE
[1] "1.4"
[1] 22
[1] TRUE
[1] "2.08"
[1] 23
[1] TRUE
[1] "1.6"
[1] 24
[1] TRUE
[1] "2.2000000000000002"
[1] 25
[1] TRUE
[1] "5.3"
[1] 26
[1] TRUE
[1] "5.3"
[1] 27
[1] TRUE
[1] "5.3"
[1] 28
[1] TRUE
[1] "5.3"
[1] 29
[1] TRUE
[1] "7.3"
[1] 30
[1] TRUE
[1] "7.3"
[1] 31
[1] TRUE
[1] "6.3"
[1] 32
[1] TRUE
[1] "6.3"
[1] 33
[1] TRUE
[1] "1.8"
[1] 34
[1] TRUE
[1] "1.8"
[1] 35
[1] TRUE
[1] "1.8"
[1] 36
[1] TRUE
[1] "1.8"
[1] 37
[1] TRUE
[1] "2.4"
[1] 38
[1] TRUE
[1] "2.4"
[1] 39
[1] TRUE
[1] "2.1"
[1] 40
[1] TRUE
[1] "2.1"
[1] 41
[1] TRUE
[1] "1.3"
[1] 42
[1] TRUE
[1] "1.3"
[1] 43
[1] TRUE
[1] "1.2"
[1] 44
[1] TRUE
[1] "1.2"
[1] 45
[1] TRUE
[1] "5.0999999999999996"
[1] 46
[1] TRUE
[1] "5.0999999999999996"
[1] 47
[1] TRUE
[1] "5.0999999999999996"
[1] 48
[1] TRUE
[1] "5.0999999999999996"
[1] 49
[1] TRUE
[1] "7"
[1] 50
[1] TRUE
[1] "7"
[1] 51
[1] TRUE
[1] "5.4"
[1] 52
[1] TRUE
[1] "5.4"
[1] 53
[1] TRUE
[1] "1.4"
[1] 54
[1] TRUE
[1] "1.4"
[1] 55
[1] TRUE
[1] "1.2"
[1] 56
[1] TRUE
[1] "1.2"
[1] 57
[1] TRUE
[1] "3.6"
[1] 58
[1] TRUE
[1] "3.6"
[1] 59
[1] TRUE
[1] "3.1"
[1] 60
[1] TRUE
[1] "3.1"
[1] 61
[1] TRUE
[1] "12.7"
[1] 62
[1] TRUE
[1] "12.7"
[1] 63
[1] TRUE
[1] "12.7"
[1] 64
[1] TRUE
[1] "12.7"
[1] 65
[1] TRUE
[1] "12.7"
[1] 66
[1] TRUE
[1] "12.7"
[1] 67
[1] TRUE
[1] "17.399999999999999"
[1] 68
[1] TRUE
[1] "17.399999999999999"
[1] 69
[1] TRUE
[1] "17.399999999999999"
[1] 70
[1] TRUE
[1] "15.1"
[1] 71
[1] TRUE
[1] "15.1"
[1] 72
[1] TRUE
[1] "15.1"
[1] 73
[1] TRUE
[1] "6.3"
[1] 74
[1] TRUE
[1] "6.3"
[1] 75
[1] TRUE
[1] "6.3"
[1] 76
[1] TRUE
[1] "6.3"
[1] 77
[1] TRUE
[1] "6.3"
[1] 78
[1] TRUE
[1] "6.3"
[1] 79
[1] TRUE
[1] "8.6"
[1] 80
[1] TRUE
[1] "8.6"
[1] 81
[1] TRUE
[1] "8.6"
[1] 82
[1] TRUE
[1] "7.5"
[1] 83
[1] TRUE
[1] "7.5"
[1] 84
[1] TRUE
[1] "7.5"
[1] 85
[1] TRUE
[1] "10.7"
[1] 86
[1] TRUE
[1] "10.7"
[1] 87
[1] TRUE
[1] "10.7"
[1] 88
[1] TRUE
[1] "10.7"
[1] 89
[1] TRUE
[1] "14.7"
[1] 90
[1] TRUE
[1] "14.7"
[1] 91
[1] TRUE
[1] "12.8"
[1] 92
[1] TRUE
[1] "12.8"
[1] 93
[1] TRUE
[1] "5.8"
[1] 94
[1] TRUE
[1] "5.8"
[1] 95
[1] TRUE
[1] "5.8"
[1] 96
[1] TRUE
[1] "5.8"
[1] 97
[1] TRUE
[1] "7.9"
[1] 98
[1] TRUE
[1] "7.9"
[1] 99
[1] TRUE
[1] "3.7"
[1] 100
[1] TRUE
[1] "3.7"
[1] 101
[1] TRUE
[1] "6"
[1] 102
[1] TRUE
[1] "6"
[1] 103
[1] TRUE
[1] "6"
[1] 104
[1] TRUE
[1] "6"
[1] 105
[1] TRUE
[1] "8.1999999999999993"
[1] 106
[1] TRUE
[1] "8.1999999999999993"
[1] 107
[1] TRUE
[1] "5"
[1] 108
[1] TRUE
[1] "5"
[1] 109
[1] TRUE
[1] "3.2"
[1] 110
[1] TRUE
[1] "3.2"
[1] 111
[1] TRUE
[1] "3.9"
[1] 112
[1] TRUE
[1] "3.9"
[1] 113
[1] TRUE
[1] "16.7"
[1] 114
[1] TRUE
[1] "16.7"
[1] 115
[1] TRUE
[1] "16.7"
[1] 116
[1] TRUE
[1] "16.7"
[1] 117
[1] TRUE
[1] "18.600000000000001"
[1] 118
[1] TRUE
[1] "18.600000000000001"
[1] 119
[1] TRUE
[1] "19.600000000000001"
[1] 120
[1] TRUE
[1] "19.600000000000001"
[1] 121
[1] TRUE
[1] "22.8"
[1] 122
[1] TRUE
[1] "22.8"
[1] 123
[1] TRUE
[1] "22.8"
[1] 124
[1] TRUE
[1] "22.8"
[1] 125
[1] TRUE
[1] "25.4"
[1] 126
[1] TRUE
[1] "25.4"
[1] 127
[1] TRUE
[1] "26.8"
[1] 128
[1] TRUE
[1] "26.8"
[1] 129
[1] TRUE
[1] "2.9"
[1] 130
[1] TRUE
[1] "2.9"
[1] 131
[1] TRUE
[1] "2.9"
[1] 132
[1] TRUE
[1] "2.9"
[1] 133
[1] TRUE
[1] "2.9"
[1] 134
[1] TRUE
[1] "2.9"
[1] 135
[1] TRUE
[1] "2.9"
[1] 136
[1] TRUE
[1] "2.9"
[1] 137
[1] TRUE
[1] "2.9"
[1] 138
[1] TRUE
[1] "2.9"
[1] 139
[1] TRUE
[1] "2.9"
[1] 140
[1] TRUE
[1] "2.9"
[1] 141
[1] TRUE
[1] "1.9"
[1] 142
[1] TRUE
[1] "1.9"
[1] 143
[1] TRUE
[1] "1.9"
[1] 144
[1] TRUE
[1] "1.6"
[1] 145
[1] TRUE
[1] "1.6"
[1] 146
[1] TRUE
[1] "1.6"
[1] 147
[1] TRUE
[1] "1.6"
[1] 148
[1] TRUE
[1] "1.6"
[1] 149
[1] TRUE
[1] "1.6"
[1] 150
[1] TRUE
[1] "1.9"
[1] 151
[1] TRUE
[1] "1.9"
[1] 152
[1] TRUE
[1] "1.9"
[1] 153
[1] TRUE
[1] "0.4"
[1] 154
[1] TRUE
[1] "0.4"
[1] 155
[1] TRUE
[1] "0.4"
[1] 156
[1] TRUE
[1] "0.4"
[1] 157
[1] TRUE
[1] "0.6"
[1] 158
[1] TRUE
[1] "0.6"
[1] 159
[1] TRUE
[1] "0.5"
[1] 160
[1] TRUE
[1] "0.5"
[1] 161
[1] TRUE
[1] "14.5"
[1] 162
[1] TRUE
[1] "14.5"
[1] 163
[1] TRUE
[1] "16"
[1] 164
[1] TRUE
[1] "16"
[1] 165
[1] TRUE
[1] "16"
[1] 166
[1] TRUE
[1] "16"
[1] 167
[1] TRUE
[1] "22"
[1] 168
[1] TRUE
[1] "22"
[1] 169
[1] TRUE
[1] "19.100000000000001"
[1] 170
[1] TRUE
[1] "19.100000000000001"
[1] 171
[1] TRUE
[1] "1.6"
[1] 172
[1] TRUE
[1] "1.6"
[1] 173
[1] TRUE
[1] "1.6"
[1] 174
[1] TRUE
[1] "1.6"
[1] 175
[1] TRUE
[1] "2.2000000000000002"
[1] 176
[1] TRUE
[1] "2.2000000000000002"
[1] 177
[1] TRUE
[1] "2.2000000000000002"
[1] 178
[1] TRUE
[1] "2.2000000000000002"
[1] 179
[1] TRUE
[1] "4.4000000000000004"
[1] 180
[1] TRUE
[1] "4.4000000000000004"
[1] 181
[1] TRUE
[1] "4.4000000000000004"
[1] 182
[1] TRUE
[1] "4.4000000000000004"
[1] 183
[1] TRUE
[1] "6"
[1] 184
[1] TRUE
[1] "6"
[1] 185
[1] TRUE
[1] "5.2"
[1] 186
[1] TRUE
[1] "5.2"
[1] 187
[1] TRUE
[1] "24.6"
[1] 188
[1] TRUE
[1] "24.6"
[1] 189
[1] TRUE
[1] "24.6"
[1] 190
[1] TRUE
[1] "24.6"
[1] 191
[1] TRUE
[1] "33.700000000000003"
[1] 192
[1] TRUE
[1] "33.700000000000003"
[1] 193
[1] TRUE
[1] "29.3"
[1] 194
[1] TRUE
[1] "29.3"
[1] 195
[1] TRUE
[1] "8.4"
[1] 196
[1] TRUE
[1] "8.4"
[1] 197
[1] TRUE
[1] "8.4"
[1] 198
[1] TRUE
[1] "8.4"
[1] 199
[1] TRUE
[1] "11.6"
[1] 200
[1] TRUE
[1] "11.6"
[1] 201
[1] TRUE
[1] "10"
[1] 202
[1] TRUE
[1] "10"
[1] 203
[1] TRUE
[1] "1"
[1] 204
[1] TRUE
[1] "1"
[1] 205
[1] TRUE
[1] "1"
[1] 206
[1] TRUE
[1] "1"
[1] 207
[1] TRUE
[1] "1"
[1] 208
[1] TRUE
[1] "1"
[1] 209
[1] TRUE
[1] "1.4"
[1] 210
[1] TRUE
[1] "1.4"
[1] 211
[1] TRUE
[1] "1.4"
[1] 212
[1] TRUE
[1] "1.2"
[1] 213
[1] TRUE
[1] "1.2"
[1] 214
[1] TRUE
[1] "1.2"
[1] 215
[1] TRUE
[1] "1"
[1] 216
[1] TRUE
[1] "1"
[1] 217
[1] TRUE
[1] "1.1000000000000001"
[1] 218
[1] TRUE
[1] "1.1000000000000001"
[1] 219
[1] TRUE
[1] "11.7"
[1] 220
[1] TRUE
[1] "11.7"
[1] 221
[1] TRUE
[1] "11.7"
[1] 222
[1] TRUE
[1] "11.7"
[1] 223
[1] TRUE
[1] "0.8"
[1] 224
[1] TRUE
[1] "0.8"
[1] 225
[1] TRUE
[1] "0.6"
[1] 226
[1] TRUE
[1] "0.6"
[1] 227
[1] TRUE
[1] "0.8"
[1] 228
[1] TRUE
[1] "0.8"
[1] 229
[1] TRUE
[1] "0.5"
[1] 230
[1] TRUE
[1] "0.5"
[1] 231
[1] TRUE
[1] "0.6"
[1] 232
[1] TRUE
[1] "0.6"
[1] 233
[1] TRUE
[1] "0.7"
[1] 234
[1] TRUE
[1] "0.7"
[1] 235
[1] TRUE
[1] "0.7"
[1] 236
[1] TRUE
[1] "0.8"
[1] 237
[1] TRUE
[1] "1"
[1] 238
[1] TRUE
[1] "1"
[1] 239
[1] TRUE
[1] "1.2"
[1] 240
[1] TRUE
[1] "1.5"
[1] 241
[1] TRUE
[1] "1.5"
[1] 242
[1] TRUE
[1] "2.2000000000000002"
[1] 243
[1] TRUE
[1] "2.2000000000000002"
[1] 244
[1] TRUE
[1] "2.9"
[1] 245
[1] TRUE
[1] "2.9"
[1] 246
[1] TRUE
[1] "2.2999999999999998"
[1] 247
[1] TRUE
[1] "2.2999999999999998"
[1] 248
[1] TRUE
[1] "0.6"
[1] 249
[1] TRUE
[1] "0.6"
[1] 250
[1] TRUE
[1] "0.9"
[1] 251
[1] TRUE
[1] "0.9"
[1] 252
[1] TRUE
[1] "0.9"
[1] 253
[1] TRUE
[1] "1.1000000000000001"
[1] 254
[1] TRUE
[1] "0.7"
[1] 255
[1] TRUE
[1] "0.7"
[1] 256
[1] TRUE
[1] "1.1000000000000001"
[1] 257
[1] TRUE
[1] "1.1000000000000001"
[1] 258
[1] TRUE
[1] "0.8"
[1] 259
[1] TRUE
[1] "0.8"
[1] 260
[1] TRUE
[1] "0.8"
[1] 261
[1] TRUE
[1] "0.8"
[1] 262
[1] TRUE
[1] "1.2"
[1] 263
[1] TRUE
[1] "0.8"
[1] 264
[1] TRUE
[1] "0.8"
[1] 265
[1] TRUE
[1] "1.2"
[1] 266
[1] TRUE
[1] "1.2"
[1] 267
[1] TRUE
[1] "1.5"
[1] 268
[1] TRUE
[1] "8.9"
[1] 269
[1] TRUE
[1] "8.9"
[1] 270
[1] TRUE
[1] "8.9"
[1] 271
[1] TRUE
[1] "1"
[1] 272
[1] TRUE
[1] "1"
[1] 273
[1] TRUE
[1] "1.5"
[1] 274
[1] TRUE
[1] "1.5"
[1] 275
[1] TRUE
[1] "6.2"
[1] 276
[1] TRUE
[1] "6.2"
[1] 277
[1] TRUE
[1] "5"
[1] 278
[1] TRUE
[1] "5"
[1] 279
[1] TRUE
[1] "5.5"
[1] 280
[1] TRUE
[1] "5.5"
[1] 281
[1] TRUE
[1] "10.1"
[1] 282
[1] TRUE
[1] "10.1"
[1] 283
[1] TRUE
[1] "10.1"
[1] 284
[1] TRUE
[1] "2.6"
[1] 285
[1] TRUE
[1] "2.6"
[1] 286
[1] TRUE
[1] "2.6"
[1] 287
[1] TRUE
[1] "5.8"
[1] 288
[1] TRUE
[1] "5.8"
[1] 289
[1] TRUE
[1] "5.8"
[1] 290
[1] TRUE
[1] "4.3"
[1] 291
[1] "3.76"
[1] 292
[1] "3.76"
[1] 293
[1] "3.76"
[1] 294
[1] "3.76"
[1] 295
[1] "2.7"
[1] 296
[1] "2.7"
[1] 297
[1] "2.7"
[1] 298
[1] "2.7"
[1] 299
[1] "2.7"
[1] 300
[1] "2.7"
[1] 301
[1] "11.701666666666668"
[1] 302
[1] "11.701666666666668"
[1] 303
[1] "11.701666666666668"
[1] 304
[1] "11.701666666666668"
[1] 305
[1] "11.701666666666668"
[1] 306
[1] "11.701666666666668"
[1] 307
[1] "11.701666666666668"
[1] 308
[1] "11.701666666666668"
[1] 309
[1] "7.6449999999999996"
[1] 310
[1] "7.6449999999999996"
[1] 311
[1] "7.6449999999999996"
[1] 312
[1] "7.6449999999999996"
[1] 313
[1] "2.5924999999999998"
[1] 314
[1] "2.5924999999999998"
[1] 315
[1] "2.5924999999999998"
[1] 316
[1] "2.5924999999999998"
[1] 317
[1] "2.5924999999999998"
[1] 318
[1] "2.5924999999999998"
[1] 319
[1] "2.5924999999999998"
[1] 320
[1] "2.5924999999999998"
[1] 321
[1] "4.74"
[1] 322
[1] "4.74"
[1] 323
[1] "4.74"
[1] 324
[1] "4.74"
[1] 325
[1] "2.1074999999999999"
[1] 326
[1] "2.1074999999999999"
[1] 327
[1] "2.1074999999999999"
[1] 328
[1] "2.1074999999999999"
[1] 329
[1] "1"
[1] 330
[1] "1"
[1] 331
[1] "1"
[1] 332
[1] "1"
[1] 333
[1] "2.9722222222222223"
[1] 334
[1] "2.9722222222222223"
[1] 335
[1] "2.9722222222222223"
[1] 336
[1] "2.9722222222222223"
[1] 337
[1] "2.5749999999999997"
[1] 338
[1] "2.5749999999999997"
[1] 339
[1] "2.5749999999999997"
[1] 340
[1] "2.5749999999999997"
[1] 341
[1] "6.6074999999999999"
[1] 342
[1] "6.6074999999999999"
[1] 343
[1] "6.6074999999999999"
[1] 344
[1] "6.6074999999999999"
[1] 345
[1] "7.66"
[1] 346
[1] "7.66"
[1] 347
[1] "7.66"
[1] 348
[1] "7.66"
[1] 349
[1] "2.7939999999999996"
[1] 350
[1] "2.7939999999999996"
[1] 351
[1] "2.7939999999999996"
[1] 352
[1] "2.7939999999999996"
[1] 353
[1] "1.5049999999999999"
[1] 354
[1] "1.5049999999999999"
[1] 355
[1] "1.5049999999999999"
[1] 356
[1] "1.5049999999999999"
[1] 357
[1] "4.5642857142857149"
[1] 358
[1] "4.5642857142857149"
[1] 359
[1] "4.5642857142857149"
[1] 360
[1] "4.5642857142857149"
[1] 361
[1] "2.7966666666666669"
[1] 362
[1] "2.7966666666666669"
[1] 363
[1] "2.7966666666666669"
[1] 364
[1] "2.7966666666666669"
[1] 365
[1] "4.8866666666666667"
[1] 366
[1] "4.8866666666666667"
[1] 367
[1] "4.8866666666666667"
[1] 368
[1] "4.8866666666666667"
[1] 369
[1] "3.2099999999999995"
[1] 370
[1] "3.2099999999999995"
[1] 371
[1] "3.2099999999999995"
[1] 372
[1] "3.2099999999999995"
[1] 373
[1] "2.7433333333333336"
[1] 374
[1] "2.7433333333333336"
[1] 375
[1] "2.7433333333333336"
[1] 376
[1] "2.7433333333333336"
[1] 377
[1] "2.4528571428571424"
[1] 378
[1] "2.4528571428571424"
[1] 379
[1] "2.4528571428571424"
[1] 380
[1] "2.4528571428571424"
[1] 381
[1] "2.4533333333333331"
[1] 382
[1] "2.4533333333333331"
[1] 383
[1] "2.4533333333333331"
[1] 384
[1] "2.4533333333333331"
[1] 385
[1] "4.5766666666666671"
[1] 386
[1] "4.5766666666666671"
[1] 387
[1] "4.5766666666666671"
[1] 388
[1] "4.5766666666666671"
[1] 389
[1] "16.782857142857143"
[1] 390
[1] "16.782857142857143"
[1] 391
[1] "16.782857142857143"
[1] 392
[1] "16.782857142857143"
[1] 393
[1] "2.0324999999999998"
[1] 394
[1] "2.0324999999999998"
[1] 395
[1] "2.0324999999999998"
[1] 396
[1] "2.0324999999999998"
[1] 397
[1] "2.0324999999999998"
[1] 398
[1] "2.0324999999999998"
[1] 399
[1] "4.3099999999999996"
[1] 400
[1] "4.3099999999999996"
[1] 401
[1] "4.3099999999999996"
[1] 402
[1] "4.3099999999999996"
[1] 403
[1] "3.6"
[1] 404
[1] "3.6"
[1] 405
[1] "3.6"
[1] 406
[1] "3.6"
[1] 407
[1] "3.6"
[1] 408
[1] "3.6"
[1] 409
[1] "5.21"
[1] 410
[1] "5.21"
[1] 411
[1] "5.21"
[1] 412
[1] "5.21"
[1] 413
[1] "3.0350000000000001"
[1] 414
[1] "3.0350000000000001"
[1] 415
[1] "3.0350000000000001"
[1] 416
[1] "3.0350000000000001"
[1] 417
[1] "1.5449999999999999"
[1] 418
[1] "1.5449999999999999"
[1] 419
[1] "10.962999999999999"
[1] 420
[1] "10.962999999999999"
[1] 421
[1] "10.962999999999999"
[1] 422
[1] "10.962999999999999"
[1] 423
[1] "1.25"
[1] 424
[1] "1.25"
[1] 425
[1] "2.0350000000000001"
[1] 426
[1] "2.0350000000000001"
[1] 427
[1] "2.9140000000000001"
[1] 428
[1] "2.9140000000000001"
[1] 429
[1] "0.57999999999999996"
[1] 430
[1] "0.57999999999999996"
[1] 431
[1] "3.258"
[1] 432
[1] "3.258"
[1] 433
[1] "0.68"
[1] 434
[1] "0.68"
[1] 435
[1] "2.6733333333333333"
[1] 436
[1] "2.6733333333333333"
[1] 437
[1] "2.6733333333333333"
[1] 438
[1] "2.6733333333333333"
[1] 439
[1] "2.5550000000000002"
[1] 440
[1] "2.5550000000000002"
[1] 441
[1] "2.5550000000000002"
[1] 442
[1] "2.5550000000000002"
[1] 443
[1] "1.42"
[1] 444
[1] "1.42"
[1] 445
[1] "5.9557142857142855"
[1] 446
[1] "5.9557142857142855"
[1] 447
[1] "5.9557142857142855"
[1] 448
[1] "5.9557142857142855"
[1] 449
[1] "3.0933333333333333"
[1] 450
[1] "3.0933333333333333"
[1] 451
[1] "3.0933333333333333"
[1] 452
[1] "3.0933333333333333"
[1] 453
[1] "2.4"
[1] 454
[1] "2.4"
[1] 455
[1] "2.4"
[1] 456
[1] "2.4"
[1] 457
[1] "3.92"
[1] 458
[1] "3.92"
[1] 459
[1] "3.92"
[1] 460
[1] "3.92"
[1] 461
[1] "3.3"
[1] 462
[1] "3.3"
[1] 463
[1] "3.3"
[1] 464
[1] "3.3"
[1] 465
[1] "3.0249999999999999"
[1] 466
[1] "3.0249999999999999"
[1] 467
[1] "3.0249999999999999"
[1] 468
[1] "3.0249999999999999"
[1] 469
[1] "1.9514285714285715"
[1] 470
[1] "1.9514285714285715"
[1] 471
[1] "1.9514285714285715"
[1] 472
[1] "1.9514285714285715"
[1] 473
[1] "1.9514285714285715"
[1] 474
[1] "1.9514285714285715"
[1] 475
[1] "4.58"
[1] 476
[1] "4.58"
[1] 477
[1] "4.58"
[1] 478
[1] "4.58"
[1] 479
[1] "100"
[1] 480
[1] "100"
[1] 481
[1] "100"
[1] 482
[1] "100"
[1] 483
[1] "100"
[1] 484
[1] "100"
[1] 485
[1] "100"
[1] 486
[1] "100"
[1] 487
[1] "1.2376666666666667"
[1] 488
[1] "1.2376666666666667"
[1] 489
[1] "0.94200000000000006"
[1] 490
[1] "0.94200000000000006"
[1] 491
[1] "0.36"
[1] 492
[1] "0.36"
[1] 493
[1] "0.36"
[1] 494
[1] "0.36"
[1] 495
[1] "1.3023333333333333"
[1] 496
[1] "1.3023333333333333"
[1] 497
[1] "5.9966666666666661"
[1] 498
[1] "5.9966666666666661"
[1] 499
[1] "5.9966666666666661"
[1] 500
[1] "0.87"
[1] 501
[1] "0.87"
[1] 502
[1] "0.87"
[1] 503
[1] "0.87"
[1] 504
[1] "0.87"
[1] 505
[1] "0.87"
[1] 506
[1] "3.6066666666666669"
[1] 507
[1] "3.6066666666666669"
[1] 508
[1] "9.9543333333333326"
[1] 509
[1] "9.9543333333333326"
[1] 510
[1] "0.74799999999999989"
[1] 511
[1] "0.74799999999999989"
[1] 512
[1] "1.0006666666666666"
[1] 513
[1] "0.501"
[1] 514
[1] "0.501"
[1] 515
[1] "0.42299999999999999"
[1] 516
[1] "5.9866666666666672"
[1] 517
[1] "5.9866666666666672"
[1] 518
[1] "5.9866666666666672"
[1] 519
[1] "5.9866666666666672"
[1] 520
[1] "19.566333333333333"
[1] 521
[1] "19.566333333333333"
[1] 522
[1] "16.933000000000003"
[1] 523
[1] "16.933000000000003"
[1] 524
[1] "2.2433333333333336"
[1] 525
[1] "2.2433333333333336"
[1] 526
[1] "2.2433333333333336"
[1] 527
[1] "2.2433333333333336"
[1] 528
[1] "3.5736666666666665"
[1] 529
[1] "3.5736666666666665"
[1] 530
[1] "2.5626666666666664"
[1] 531
[1] "2.5626666666666664"
[1] 532
[1] "5.6416666666666666"
[1] 533
[1] "5.6416666666666666"
[1] 534
[1] "5.6416666666666666"
[1] 535
[1] "5.6416666666666666"
[1] 536
[1] "6.5466666666666669"
[1] 537
[1] "6.5466666666666669"
[1] 538
[1] "6.5466666666666669"
[1] 539
[1] "6.5466666666666669"
[1] 540
[1] "22.782"
[1] 541
[1] "22.782"
[1] 542
[1] "9.397333333333334"
[1] 543
[1] "9.397333333333334"
[1] 544
[1] "9.397333333333334"
[1] 545
[1] "9.397333333333334"
[1] 546
[1] "22.593"
[1] 547
[1] "22.593"
[1] 548
[1] "24.46"
[1] 549
[1] "24.46"
[1] 550
[1] "0.92133333333333345"
[1] 551
[1] "0.92133333333333345"
[1] 552
[1] "8.4966666666666679"
[1] 553
[1] "8.4966666666666679"
[1] 554
[1] "11.777000000000001"
[1] 555
[1] "11.777000000000001"
[1] 556
[1] "19.114999999999998"
[1] 557
[1] "19.114999999999998"
[1] 558
[1] "3.57"
[1] 559
[1] "3.57"
[1] 560
[1] "3.9820000000000007"
[1] 561
[1] "3.9820000000000007"
[1] 562
[1] "1.3133333333333335"
[1] 563
[1] "1.3133333333333335"
[1] 564
[1] "1.3133333333333335"
[1] 565
[1] "1.3133333333333335"
[1] 566
[1] "2.294"
[1] 567
[1] "2.294"
[1] 568
[1] "0.61333333333333329"
[1] 569
[1] "0.61333333333333329"
[1] 570
[1] "0.61333333333333329"
[1] 571
[1] "0.61333333333333329"
[1] 572
[1] "14.035333333333334"
[1] 573
[1] "14.035333333333334"
[1] 574
[1] "9.7089999999999979"
[1] 575
[1] "9.7089999999999979"
[1] 576
[1] "14.532333333333334"
[1] 577
[1] "14.532333333333334"
[1] 578
[1] "2.9873333333333334"
[1] 579
[1] "2.9873333333333334"
[1] 580
[1] "2.9873333333333334"
[1] 581
[1] "24.048666666666666"
[1] 582
[1] "24.048666666666666"
[1] 583
[1] "24.048666666666666"
[1] 584
[1] "12.693333333333333"
[1] 585
[1] "12.693333333333333"
[1] 586
[1] "12.693333333333333"
[1] 587
[1] "2.65"
[1] 588
[1] "2.65"
[1] 589
[1] "2.65"
[1] 590
[1] "2.65"
[1] 591
[1] "2.65"
[1] 592
[1] "2.65"
[1] 593
[1] "1.22"
[1] 594
[1] "1.22"
[1] 595
[1] "1.22"
[1] 596
[1] "1.22"
[1] 597
[1] "3.2"
[1] 598
[1] "3.2"
[1] 599
[1] "3.2"
[1] 600
[1] "3.2"
[1] 601
[1] "3.2"
[1] 602
[1] "3.2"
[1] 603
[1] "7.5"
[1] 604
[1] "7.5"
[1] 605
[1] "7.5"
[1] 606
[1] "7.5"
[1] 607
[1] "12.9"
[1] 608
[1] "12.9"
[1] 609
[1] "12.9"
[1] 610
[1] "12.9"
[1] 611
[1] "12.9"
[1] 612
[1] "12.9"
[1] 613
[1] "16.2"
[1] 614
[1] "16.2"
[1] 615
[1] "16.2"
[1] 616
[1] "13.6"
[1] 617
[1] "13.6"
[1] 618
[1] "13.6"
[1] 619
[1] "13.6"
[1] 620
[1] "13.6"
[1] 621
[1] "13.6"
[1] 622
[1] "0.7"
[1] 623
[1] "0.7"
[1] 624
[1] "0.7"
[1] 625
[1] "0.7"
[1] 626
[1] "0.6"
[1] 627
[1] "0.6"
[1] 628
[1] "0.6"
[1] 629
[1] "0.6"
[1] 630
[1] "0.3"
[1] 631
[1] "3.7"
[1] 632
[1] "3.7"
[1] 633
[1] "1"
[1] 634
[1] "1"
[1] 635
[1] "1"
[1] 636
[1] "1"
[1] 637
[1] "0.3"
[1] 638
[1] "0.3"
[1] 639
[1] "0.6"
[1] 640
[1] "0.6"
[1] 641
[1] "0.6"
[1] 642
[1] "0.6"
[1] 643
[1] "1.6"
[1] 644
[1] "1.6"
[1] 645
[1] "1.6"
[1] 646
[1] "1.6"
[1] 647
[1] "0.2"
[1] 648
[1] "0.2"
[1] 649
[1] "0.2"
[1] 650
[1] "0.2"
[1] 651
[1] "1.1000000000000001"
[1] 652
[1] "1.1000000000000001"
[1] 653
[1] "1.1000000000000001"
[1] 654
[1] "1.1000000000000001"
[1] 655
[1] "3"
[1] 656
[1] "1"
[1] 657
[1] "1"
[1] 658
[1] "1"
[1] 659
[1] "1"
[1] 660
[1] "1"
[1] 661
[1] "1"
[1] 662
[1] "3"
[1] 663
[1] "3"
[1] 664
[1] "3"
[1] 665
[1] "3"
[1] 666
[1] "2.4"
[1] 667
[1] "2.6"
[1] 668
[1] "1.2"
[1] 669
[1] "1.2"
[1] 670
[1] "1.2"
[1] 671
[1] "7.8"
[1] 672
[1] "7.8"
[1] 673
[1] "7.8"
[1] 674
[1] "7.8"
[1] 675
[1] "10.5"
[1] 676
[1] "10.5"
[1] 677
[1] "10.5"
[1] 678
[1] "10.5"
[1] 679
[1] "10.5"
[1] 680
[1] "10.5"
[1] 681
[1] "14.3"
[1] 682
[1] "14.3"
[1] 683
[1] "14.3"
[1] 684
[1] "14.3"
[1] 685
[1] "8.9"
[1] 686
[1] "8.9"
[1] 687
[1] "8.9"
[1] 688
[1] "8.9"
[1] 689
[1] "1.1000000000000001"
[1] 690
[1] "1.1000000000000001"
[1] 691
[1] "1.1000000000000001"
[1] 692
[1] "1.1000000000000001"
[1] 693
[1] "1.1000000000000001"
[1] 694
[1] "1.1000000000000001"
[1] 695
[1] "8.1999999999999993"
[1] 696
[1] "8.1999999999999993"
[1] 697
[1] "8"
[1] 698
[1] "8"
[1] 699
[1] "8"
[1] 700
[1] "10.3"
[1] 701
[1] "10.3"
[1] 702
[1] "10.3"
[1] 703
[1] "16"
[1] 704
[1] "16"
[1] 705
[1] "16"
[1] 706
[1] "16"
[1] 707
[1] "16"
[1] 708
[1] "16"
[1] 709
[1] "8.4"
[1] 710
[1] "8.4"
[1] 711
[1] "8.4"
[1] 712
[1] "16.100000000000001"
[1] 713
[1] "16.100000000000001"
[1] 714
[1] "14.9"
[1] 715
[1] "14.9"
[1] 716
[1] "14.9"
[1] 717
[1] "10.4"
[1] 718
[1] "10.4"
[1] 719
[1] "10.4"
[1] 720
[1] "16.399999999999999"
[1] 721
[1] "16.399999999999999"
[1] 722
[1] "16.399999999999999"
[1] 723
[1] "23.5"
[1] 724
[1] "23.5"
[1] 725
[1] "23.5"
[1] 726
[1] "10.3"
[1] 727
[1] "10.3"
[1] 728
[1] "10.3"
[1] 729
[1] "0.5"
[1] 730
[1] "25.3"
[1] 731
[1] "25.3"
[1] 732
[1] "25.3"
[1] 733
[1] "27.7"
[1] 734
[1] "27.7"
[1] 735
[1] "27.7"
[1] 736
[1] "27.7"
[1] 737
[1] "27.8"
[1] 738
[1] "27.8"
[1] 739
[1] "27.8"
[1] 740
[1] "100"
[1] 741
[1] "100"
[1] 742
[1] "100"
[1] 743
[1] "100"
[1] 744
[1] "100"
[1] 745
[1] "100"
[1] 746
[1] "100"
[1] 747
[1] "100"
[1] 748
[1] "99.9"
[1] 749
[1] "99.9"
[1] 750
[1] "99.9"
[1] 751
[1] "99.9"
[1] 752
[1] "99.9"
[1] 753
[1] "99.9"
[1] 754
[1] "99.9"
[1] 755
[1] "99.9"
[1] 756
[1] "8.9"
[1] 757
[1] "8.9"
[1] 758
[1] "8.9"
[1] 759
[1] "20.7"
[1] 760
[1] "20.7"
[1] 761
[1] "20.7"
[1] 762
[1] "1.7"
[1] 763
[1] "1.7"
[1] 764
[1] "1.7"
[1] 765
[1] "1.7"
[1] 766
[1] "1.7"
[1] 767
[1] "1.7"
[1] 768
[1] "18.3"
[1] 769
[1] "18.3"
[1] 770
[1] "18.3"
[1] 771
[1] "18.3"
[1] 772
[1] "2.2999999999999998"
[1] 773
[1] "2.2999999999999998"
[1] 774
[1] "2.2999999999999998"
[1] 775
[1] "2.2999999999999998"
[1] 776
[1] "0.98"
[1] 777
[1] "0.98"
[1] 778
[1] "1.8"
[1] 779
[1] "1.8"
[1] 780
[1] "1.8"
[1] 781
[1] "1.8"
[1] 782
[1] "0.78"
[1] 783
[1] "0.78"
[1] 784
[1] "0.78"
[1] 785
[1] "0.78"
[1] 786
[1] "1.11"
[1] 787
[1] "1.11"
[1] 788
[1] "0.29"
[1] 789
[1] "0.29"
[1] 790
[1] "0.29"
[1] 791
[1] "0.29"
[1] 792
[1] "1.03"
[1] 793
[1] "1.03"
[1] 794
[1] "2.87"
[1] 795
[1] "2.87"
[1] 796
[1] "2.13"
[1] 797
[1] "2.13"
[1] 798
[1] "1.68"
[1] 799
[1] "1.68"
[1] 800
[1] "1.68"
[1] 801
[1] "1.68"
[1] 802
[1] "0.67"
[1] 803
[1] "0.67"
[1] 804
[1] "0.7"
[1] 805
[1] "0.7"
[1] 806
[1] "0.7"
[1] 807
[1] "0.7"
[1] 808
[1] "2.02"
[1] 809
[1] "2.02"
[1] 810
[1] "0.88"
[1] 811
[1] "0.88"
[1] 812
[1] "0.44"
[1] 813
[1] "0.44"
[1] 814
[1] "18.49"
[1] 815
[1] "18.49"
[1] 816
[1] "18.49"
[1] 817
[1] "18.49"
[1] 818
[1] "1.46"
[1] 819
[1] "1.46"
[1] 820
[1] "1.92"
[1] 821
[1] "1.92"
[1] 822
[1] "1.34"
[1] 823
[1] "1.34"
[1] 824
[1] "4.2"
[1] 825
[1] "4.2"
[1] 826
[1] "4.54"
[1] 827
[1] "4.54"
[1] 828
[1] "1.2"
[1] 829
[1] "1.2"
[1] 830
[1] "1.27"
[1] 831
[1] "1.27"
[1] 832
[1] "1.27"
[1] 833
[1] "1.27"
[1] 834
[1] "1.38"
[1] 835
[1] "1.38"
[1] 836
[1] "1.38"
[1] 837
[1] "1.38"
[1] 838
[1] "0.84"
[1] 839
[1] "0.84"
[1] 840
[1] "0.84"
[1] 841
[1] "0.84"
[1] 842
[1] "3"
[1] 843
[1] "3"
[1] 844
[1] "3"
[1] 845
[1] "3"
[1] 846
[1] "4.7"
[1] 847
[1] "4.7"
[1] 848
[1] "4.7"
[1] 849
[1] "4.7"
[1] 850
[1] "0.56"
[1] 851
[1] "0.56"
[1] 852
[1] "3.36"
[1] 853
[1] "3.36"
[1] 854
[1] "3.6"
[1] 855
[1] "3.6"
[1] 856
[1] "3.6"
[1] 857
[1] "3.6"
[1] 858
[1] "0.67"
[1] 859
[1] "0.67"
[1] 860
[1] "1.53"
[1] 861
[1] "1.53"
[1] 862
[1] "1.53"
[1] 863
[1] "1.53"
[1] 864
[1] "0.79"
[1] 865
[1] "0.79"
[1] 866
[1] "1.09"
[1] 867
[1] "1.09"
[1] 868
[1] "1.09"
[1] 869
[1] "1.09"
[1] 870
[1] "4.69"
[1] 871
[1] "4.69"
[1] 872
[1] "1.32"
[1] 873
[1] "1.32"
[1] 874
[1] "0.58"
[1] 875
[1] "0.58"
[1] 876
[1] "0.58"
[1] 877
[1] "0.58"
[1] 878
[1] "0.56"
[1] 879
[1] "0.56"
[1] 880
[1] "0.56"
[1] 881
[1] "0.56"
[1] 882
[1] "0.72"
[1] 883
[1] "0.72"
[1] 884
[1] "1.6"
[1] 885
[1] "1.6"
[1] 886
[1] "1.6"
[1] 887
[1] "1.6"
[1] 888
[1] "1.84"
[1] 889
[1] "1.84"
[1] 890
[1] "1.84"
[1] 891
[1] "1.84"
[1] 892
[1] "0.69"
[1] 893
[1] "0.69"
[1] 894
[1] "1.81"
[1] 895
[1] "1.81"
[1] 896
[1] "4.44"
[1] 897
[1] "4.44"
[1] 898
[1] "2.74"
[1] 899
[1] "2.74"
[1] 900
[1] "2.74"
[1] 901
[1] "2.74"
[1] 902
[1] "0.62"
[1] 903
[1] "0.62"
[1] 904
[1] "0.57"
[1] 905
[1] "0.57"
[1] 906
[1] "0.87"
[1] 907
[1] "0.87"
[1] 908
[1] "1.33"
[1] 909
[1] "1.33"
[1] 910
[1] "1.33"
[1] 911
[1] "1.33"
[1] 912
[1] "4.83"
[1] 913
[1] "4.83"
[1] 914
[1] "4.83"
[1] 915
[1] "4.83"
[1] 916
[1] "0.46"
[1] 917
[1] "0.46"
[1] 918
[1] "0.46"
[1] 919
[1] "0.46"
[1] 920
[1] "5.12"
[1] 921
[1] "5.12"
[1] 922
[1] "5.12"
[1] 923
[1] "5.12"
[1] 924
[1] "1.89"
[1] 925
[1] "1.89"
[1] 926
[1] "1.55"
[1] 927
[1] "1.55"
[1] 928
[1] "1.55"
[1] 929
[1] "1.55"
[1] 930
[1] "1.17"
[1] 931
[1] "1.17"
[1] 932
[1] "1.17"
[1] 933
[1] "1.17"
[1] 934
[1] "1.69"
[1] 935
[1] "1.69"
[1] 936
[1] "2.17"
[1] 937
[1] "2.17"
[1] 938
[1] "0.7"
[1] 939
[1] "0.7"
[1] 940
[1] "1.34"
[1] 941
[1] "1.34"
[1] 942
[1] "2.3"
[1] 943
[1] "2.3"
[1] 944
[1] "2.97"
[1] 945
[1] "2.97"
[1] 946
[1] "9.86"
[1] 947
[1] "9.86"
[1] 948
[1] "9.86"
[1] 949
[1] "9.86"
[1] 950
[1] "2.67"
[1] 951
[1] "2.67"
[1] 952
[1] "1.68"
[1] 953
[1] "1.68"
[1] 954
[1] "1.68"
[1] 955
[1] "1.68"
[1] 956
[1] "8.99"
[1] 957
[1] "8.99"
[1] 958
[1] "8.99"
[1] 959
[1] "8.99"
[1] 960
[1] "0.83"
[1] 961
[1] "0.83"
[1] 962
[1] "0.8"
[1] 963
[1] "0.8"
[1] 964
[1] "0.75"
[1] 965
[1] "0.75"
[1] 966
[1] "1.74"
[1] 967
[1] "1.74"
[1] 968
[1] "1.74"
[1] 969
[1] "1.74"
[1] 970
[1] "6.68"
[1] 971
[1] "6.68"
[1] 972
[1] "6.68"
[1] 973
[1] "6.68"
[1] 974
[1] "1.53"
[1] 975
[1] "1.53"
[1] 976
[1] "5.17"
[1] 977
[1] "5.17"
[1] 978
[1] "5.17"
[1] 979
[1] "5.17"
[1] 980
[1] "1.18"
[1] 981
[1] "1.18"
[1] 982
[1] "0.68"
[1] 983
[1] "0.68"
[1] 984
[1] "1.2"
[1] 985
[1] "1.2"
[1] 986
[1] "2.13"
[1] 987
[1] "2.13"
[1] 988
[1] "1.08"
[1] 989
[1] "1.08"
[1] 990
[1] "1.08"
[1] 991
[1] "1.08"
[1] 992
[1] "1.44"
[1] 993
[1] "1.44"
[1] 994
[1] "1.44"
[1] 995
[1] "1.44"
[1] 996
[1] "1.12"
[1] 997
[1] "1.12"
[1] 998
[1] "1.12"
[1] 999
[1] "1.12"
[1] 1000
[1] "1.06"
[1] 1001
[1] "1.06"
[1] 1002
[1] "1.06"
[1] 1003
[1] "1.06"
[1] 1004
[1] "5.18"
[1] 1005
[1] "5.18"
[1] 1006
[1] "5.18"
[1] 1007
[1] "5.18"
[1] 1008
[1] "4.34"
[1] 1009
[1] "4.34"
[1] 1010
[1] "2.14"
[1] 1011
[1] "2.14"
[1] 1012
[1] "0.82"
[1] 1013
[1] "0.82"
[1] 1014
[1] "0.88"
[1] 1015
[1] "0.88"
[1] 1016
[1] "0.88"
[1] 1017
[1] "0.88"
[1] 1018
[1] "1.41"
[1] 1019
[1] "1.41"
[1] 1020
[1] "0.6"
[1] 1021
[1] "0.6"
[1] 1022
[1] "0.56"
[1] 1023
[1] "0.56"
[1] 1024
[1] "0.78"
[1] 1025
[1] "0.78"
[1] 1026
[1] "0.55"
[1] 1027
[1] "0.55"
[1] 1028
[1] "2.44"
[1] 1029
[1] "2.44"
[1] 1030
[1] "0.56"
[1] 1031
[1] "0.56"
[1] 1032
[1] "0.74"
[1] 1033
[1] "0.74"
[1] 1034
[1] "0.98"
[1] 1035
[1] "0.98"
[1] 1036
[1] "1.34"
[1] 1037
[1] "1.34"
[1] 1038
[1] "1.12"
[1] 1039
[1] "1.12"
[1] 1040
[1] "1.07"
[1] 1041
[1] "1.07"
[1] 1042
[1] "0.93"
[1] 1043
[1] "0.93"
[1] 1044
[1] "1.44"
[1] 1045
[1] "1.44"
[1] 1046
[1] "1.15"
[1] 1047
[1] "1.15"
[1] 1048
[1] "6.24"
[1] 1049
[1] "6.24"
[1] 1050
[1] "6.24"
[1] 1051
[1] "6.24"
[1] 1052
[1] "2.15"
[1] 1053
[1] "2.15"
[1] 1054
[1] "2.15"
[1] 1055
[1] "2.15"
[1] 1056
[1] "2.63"
[1] 1057
[1] "2.63"
[1] 1058
[1] "2.63"
[1] 1059
[1] "2.63"
[1] 1060
[1] "2.94"
[1] 1061
[1] "2.94"
[1] 1062
[1] "2.94"
[1] 1063
[1] "2.94"
[1] 1064
[1] "16.77"
[1] 1065
[1] "16.77"
[1] 1066
[1] "16.77"
[1] 1067
[1] "16.77"
[1] 1068
[1] "2.39"
[1] 1069
[1] "2.39"
[1] 1070
[1] "2.39"
[1] 1071
[1] "2.39"
[1] 1072
[1] "0.89"
[1] 1073
[1] "0.89"
[1] 1074
[1] "0.52"
[1] 1075
[1] "0.52"
[1] 1076
[1] "0.78"
[1] 1077
[1] "0.78"
[1] 1078
[1] "0.66"
[1] 1079
[1] "0.66"
[1] 1080
[1] TRUE
[1] "0.6"
[1] 1081
[1] TRUE
[1] "5.2"
[1] 1082
[1] TRUE
[1] "3.7"
[1] 1083
[1] TRUE
[1] "0.7"
[1] 1084
[1] TRUE
[1] "0.7"
[1] 1085
[1] TRUE
[1] "0.1"
[1] 1086
[1] TRUE
[1] "0.1"
[1] 1087
[1] TRUE
[1] "1.6"
[1] 1088
[1] TRUE
[1] "1.0"
[1] 1089
[1] TRUE
[1] "0.5"
[1] 1090
[1] TRUE
[1] "1.5"
[1] 1091
[1] TRUE
[1] "1.7"
[1] 1092
[1] TRUE
[1] "1.9"
[1] 1093
[1] TRUE
[1] "2.0"
[1] 1094
[1] TRUE
[1] "0.5"
[1] 1095
[1] TRUE
[1] "0.9"
[1] 1096
[1] TRUE
[1] "1.0"
[1] 1097
[1] TRUE
[1] "0.2"
[1] 1098
[1] TRUE
[1] "0.3"
[1] 1099
[1] TRUE
[1] "3.2"
[1] 1100
[1] TRUE
[1] "3.2"
[1] 1101
[1] TRUE
[1] "1.0"
[1] 1102
[1] TRUE
[1] "1.0"
[1] 1103
[1] TRUE
[1] "4.9000000000000004"
[1] 1104
[1] TRUE
[1] "0.2"
[1] 1105
[1] TRUE
[1] "1.6"
[1] 1106
[1] TRUE
[1] "1.2"
[1] 1107
[1] TRUE
[1] "4.0"
[1] 1108
[1] TRUE
[1] "0.6"
[1] 1109
[1] TRUE
[1] "4.5"
[1] 1110
[1] TRUE
[1] "4.5"
[1] 1111
[1] TRUE
[1] "4.5"
[1] 1112
[1] TRUE
[1] "4.5"
[1] 1113
[1] TRUE
[1] "4.5"
[1] 1114
[1] TRUE
[1] "4.5"
[1] 1115
[1] TRUE
[1] "5.9"
[1] 1116
[1] TRUE
[1] "5.9"
[1] 1117
[1] TRUE
[1] "5.9"
[1] 1118
[1] TRUE
[1] "6.4"
[1] 1119
[1] TRUE
[1] "6.4"
[1] 1120
[1] TRUE
[1] "6.4"
[1] 1121
[1] TRUE
[1] "18.2"
[1] 1122
[1] TRUE
[1] "18.2"
[1] 1123
[1] TRUE
[1] "18.2"
[1] 1124
[1] TRUE
[1] "5.0"
[1] 1125
[1] TRUE
[1] "5.0"
[1] 1126
[1] TRUE
[1] "5.0"
[1] 1127
[1] TRUE
[1] "5.0"
[1] 1128
[1] TRUE
[1] "5.0"
[1] 1129
[1] TRUE
[1] "5.0"
[1] 1130
[1] TRUE
[1] "18.600000000000001"
[1] 1131
[1] TRUE
[1] "18.600000000000001"
[1] 1132
[1] TRUE
[1] "18.600000000000001"
[1] 1133
[1] TRUE
[1] "5.6"
[1] 1134
[1] TRUE
[1] "5.6"
[1] 1135
[1] TRUE
[1] "5.6"
[1] 1136
[1] TRUE
[1] "5.6"
[1] 1137
[1] TRUE
[1] "5.6"
[1] 1138
[1] TRUE
[1] "5.6"
[1] 1139
[1] TRUE
[1] "7.7"
[1] 1140
[1] TRUE
[1] "7.7"
[1] 1141
[1] TRUE
[1] "7.7"
[1] 1142
[1] TRUE
[1] "9.1"
[1] 1143
[1] TRUE
[1] "9.1"
[1] 1144
[1] TRUE
[1] "9.1"
[1] 1145
[1] TRUE
[1] "9.1"
[1] 1146
[1] TRUE
[1] "9.1"
[1] 1147
[1] TRUE
[1] "9.1"
[1] 1148
[1] TRUE
[1] "8.8000000000000007"
[1] 1149
[1] TRUE
[1] "8.8000000000000007"
[1] 1150
[1] TRUE
[1] "8.8000000000000007"
[1] 1151
[1] TRUE
[1] "10.4"
[1] 1152
[1] TRUE
[1] "10.4"
[1] 1153
[1] TRUE
[1] "10.4"
[1] 1154
[1] TRUE
[1] "6.9"
[1] 1155
[1] TRUE
[1] "6.9"
[1] 1156
[1] TRUE
[1] "6.9"
[1] 1157
[1] TRUE
[1] "6.9"
[1] 1158
[1] TRUE
[1] "6.9"
[1] 1159
[1] TRUE
[1] "6.9"
[1] 1160
[1] TRUE
[1] "6.2"
[1] 1161
[1] TRUE
[1] "6.2"
[1] 1162
[1] TRUE
[1] "6.2"
[1] 1163
[1] TRUE
[1] "6.2"
[1] 1164
[1] TRUE
[1] "6.2"
[1] 1165
[1] TRUE
[1] "6.2"
[1] 1166
[1] TRUE
[1] "12.7"
[1] 1167
[1] TRUE
[1] "12.7"
[1] 1168
[1] TRUE
[1] "3.6"
[1] 1169
[1] TRUE
[1] "3.6"
[1] 1170
[1] TRUE
[1] "3.6"
[1] 1171
[1] TRUE
[1] "3.6"
[1] 1172
[1] TRUE
[1] "3.6"
[1] 1173
[1] TRUE
[1] "3.6"
[1] 1174
[1] TRUE
[1] "3.6"
[1] 1175
[1] TRUE
[1] "3.6"
[1] 1176
[1] TRUE
[1] "4.0"
[1] 1177
[1] TRUE
[1] "4.0"
[1] 1178
[1] TRUE
[1] "2.6"
[1] 1179
[1] TRUE
[1] "2.6"
[1] 1180
[1] TRUE
[1] "2.4"
[1] 1181
[1] TRUE
[1] "2.4"
[1] 1182
[1] TRUE
[1] "2.4"
[1] 1183
[1] TRUE
[1] "2.4"
[1] 1184
[1] TRUE
[1] "6.8"
[1] 1185
[1] TRUE
[1] "6.8"
[1] 1186
[1] TRUE
[1] "7.9"
[1] 1187
[1] TRUE
[1] "7.9"
[1] 1188
[1] TRUE
[1] "7.9"
[1] 1189
[1] TRUE
[1] "7.9"
[1] 1190
[1] TRUE
[1] "15.1"
[1] 1191
[1] TRUE
[1] "15.1"
[1] 1192
[1] TRUE
[1] "0.2"
[1] 1193
[1] TRUE
[1] "0.2"
[1] 1194
[1] TRUE
[1] "0.2"
[1] 1195
[1] TRUE
[1] "0.2"
[1] 1196
[1] TRUE
[1] "5.5"
[1] 1197
[1] TRUE
[1] "5.5"
[1] 1198
[1] TRUE
[1] "5.5"
[1] 1199
[1] TRUE
[1] "5.5"
[1] 1200
[1] TRUE
[1] "6.1"
[1] 1201
[1] TRUE
[1] "6.1"
[1] 1202
[1] TRUE
[1] "5.7"
[1] 1203
[1] TRUE
[1] "5.7"
[1] 1204
[1] TRUE
[1] "5.7"
[1] 1205
[1] TRUE
[1] "5.7"
[1] 1206
[1] TRUE
[1] "7.8"
[1] 1207
[1] TRUE
[1] "7.8"
[1] 1208
[1] TRUE
[1] "7.8"
[1] 1209
[1] TRUE
[1] "7.8"
[1] 1210
[1] TRUE
[1] "1.7"
[1] 1211
[1] TRUE
[1] "1.7"
[1] 1212
[1] TRUE
[1] "1.7"
[1] 1213
[1] TRUE
[1] "1.7"
[1] 1214
[1] TRUE
[1] "0.4"
[1] 1215
[1] TRUE
[1] "0.4"
[1] 1216
[1] TRUE
[1] "8.5"
[1] 1217
[1] TRUE
[1] "8.5"
[1] 1218
[1] TRUE
[1] "8.5"
[1] 1219
[1] TRUE
[1] "8.5"
[1] 1220
[1] TRUE
[1] "4.8"
[1] 1221
[1] TRUE
[1] "4.8"
[1] 1222
[1] TRUE
[1] "4.8"
[1] 1223
[1] TRUE
[1] "4.8"
[1] 1224
[1] TRUE
[1] "4.8"
[1] 1225
[1] TRUE
[1] "4.8"
[1] 1226
[1] TRUE
[1] "12.1"
[1] 1227
[1] TRUE
[1] "12.1"
[1] 1228
[1] TRUE
[1] "12.1"
[1] 1229
[1] TRUE
[1] "12.1"
[1] 1230
[1] TRUE
[1] "12.1"
[1] 1231
[1] TRUE
[1] "12.1"
[1] 1232
[1] TRUE
[1] "5.7"
[1] 1233
[1] TRUE
[1] "5.7"
[1] 1234
[1] TRUE
[1] "5.7"
[1] 1235
[1] TRUE
[1] "9.1999999999999993"
[1] 1236
[1] TRUE
[1] "9.1999999999999993"
[1] 1237
[1] TRUE
[1] "9.1999999999999993"
[1] 1238
[1] TRUE
[1] "9.1999999999999993"
[1] 1239
[1] TRUE
[1] "9.1999999999999993"
[1] 1240
[1] TRUE
[1] "9.1999999999999993"
[1] 1241
[1] TRUE
[1] "8.6999999999999993"
[1] 1242
[1] TRUE
[1] "8.6999999999999993"
[1] 1243
[1] TRUE
[1] "8.6999999999999993"
[1] 1244
[1] TRUE
[1] "9.4"
[1] 1245
[1] TRUE
[1] "9.4"
[1] 1246
[1] TRUE
[1] "9.4"
[1] 1247
[1] TRUE
[1] "30.3"
[1] 1248
[1] TRUE
[1] "30.3"
[1] 1249
[1] TRUE
[1] "30.3"
[1] 1250
[1] TRUE
[1] "15.0"
[1] 1251
[1] TRUE
[1] "15.0"
[1] 1252
[1] TRUE
[1] "15.0"
[1] 1253
[1] TRUE
[1] "1.3"
[1] 1254
[1] TRUE
[1] "1.3"
[1] 1255
[1] TRUE
[1] "1.3"
[1] 1256
[1] TRUE
[1] "1.3"
[1] 1257
[1] TRUE
[1] "1.3"
[1] 1258
[1] TRUE
[1] "1.3"
[1] 1259
[1] TRUE
[1] "5.6"
[1] 1260
[1] TRUE
[1] "5.6"
[1] 1261
[1] TRUE
[1] "5.6"
[1] 1262
[1] TRUE
[1] "10.6"
[1] 1263
[1] TRUE
[1] "10.6"
[1] 1264
[1] TRUE
[1] "10.6"
[1] 1265
[1] TRUE
[1] "11.9"
[1] 1266
[1] TRUE
[1] "11.9"
[1] 1267
[1] TRUE
[1] "11.9"
[1] 1268
[1] TRUE
[1] "10.8"
[1] 1269
[1] TRUE
[1] "10.8"
[1] 1270
[1] TRUE
[1] "10.8"
[1] 1271
[1] TRUE
[1] "30.7"
[1] 1272
[1] TRUE
[1] "30.7"
[1] 1273
[1] TRUE
[1] "30.7"
[1] 1274
[1] TRUE
[1] "15.6"
[1] 1275
[1] TRUE
[1] "15.6"
[1] 1276
[1] TRUE
[1] "15.6"
[1] 1277
[1] TRUE
[1] "6.8"
[1] 1278
[1] TRUE
[1] "6.8"
[1] 1279
[1] TRUE
[1] "6.8"
[1] 1280
[1] TRUE
[1] "3.6"
[1] 1281
[1] TRUE
[1] "3.6"
[1] 1282
[1] TRUE
[1] "3.6"
[1] 1283
[1] TRUE
[1] "3.6"
[1] 1284
[1] TRUE
[1] "1.5"
[1] 1285
[1] TRUE
[1] "1.5"
[1] 1286
[1] TRUE
[1] "1.5"
[1] 1287
[1] TRUE
[1] "1.5"
[1] 1288
[1] TRUE
[1] "19.3"
[1] 1289
[1] TRUE
[1] "19.3"
[1] 1290
[1] TRUE
[1] "19.3"
[1] 1291
[1] TRUE
[1] "19.3"
[1] 1292
[1] TRUE
[1] "0.3"
[1] 1293
[1] TRUE
[1] "0.3"
[1] 1294
[1] TRUE
[1] "0.3"
[1] 1295
[1] TRUE
[1] "0.3"
[1] 1296
[1] TRUE
[1] "0.3"
[1] 1297
[1] TRUE
[1] "0.3"
[1] 1298
[1] TRUE
[1] "0.3"
[1] 1299
[1] TRUE
[1] "0.3"
[1] 1300
[1] TRUE
[1] "0.8"
[1] 1301
[1] TRUE
[1] "0.8"
[1] 1302
[1] TRUE
[1] "0.8"
[1] 1303
[1] TRUE
[1] "0.8"
[1] 1304
[1] TRUE
[1] "5.8"
[1] 1305
[1] TRUE
[1] "5.8"
[1] 1306
[1] TRUE
[1] "5.8"
[1] 1307
[1] TRUE
[1] "5.8"
[1] 1308
[1] TRUE
[1] "1.7"
[1] 1309
[1] TRUE
[1] "1.7"
[1] 1310
[1] TRUE
[1] "1.7"
[1] 1311
[1] TRUE
[1] "1.7"
[1] 1312
[1] TRUE
[1] "0.2"
[1] 1313
[1] TRUE
[1] "0.2"
[1] 1314
[1] TRUE
[1] "0.2"
[1] 1315
[1] TRUE
[1] "0.2"
[1] 1316
[1] TRUE
[1] "0.2"
[1] 1317
[1] TRUE
[1] "0.2"
[1] 1318
[1] TRUE
[1] "1.8"
[1] 1319
[1] TRUE
[1] "1.8"
[1] 1320
[1] TRUE
[1] "1.8"
[1] 1321
[1] TRUE
[1] "1.8"
[1] 1322
[1] TRUE
[1] "1.8"
[1] 1323
[1] TRUE
[1] "1.8"
[1] 1324
[1] TRUE
[1] "7.6"
[1] 1325
[1] TRUE
[1] "7.6"
[1] 1326
[1] TRUE
[1] "7.6"
[1] 1327
[1] TRUE
[1] "7.6"
[1] 1328
[1] TRUE
[1] "7.6"
[1] 1329
[1] TRUE
[1] "7.6"
[1] 1330
[1] TRUE
[1] "11.1"
[1] 1331
[1] TRUE
[1] "11.1"
[1] 1332
[1] TRUE
[1] "11.1"
[1] 1333
[1] TRUE
[1] "0.5"
[1] 1334
[1] TRUE
[1] "0.5"
[1] 1335
[1] TRUE
[1] "0.5"
[1] 1336
[1] TRUE
[1] "0.5"
[1] 1337
[1] TRUE
[1] "0.5"
[1] 1338
[1] TRUE
[1] "0.5"
[1] 1339
[1] TRUE
[1] "6.2"
[1] 1340
[1] TRUE
[1] "6.2"
[1] 1341
[1] TRUE
[1] "6.2"
[1] 1342
[1] TRUE
[1] "6.2"
[1] 1343
[1] TRUE
[1] "6.2"
[1] 1344
[1] TRUE
[1] "6.2"
[1] 1345
[1] TRUE
[1] "2.8"
[1] 1346
[1] TRUE
[1] "2.8"
[1] 1347
[1] TRUE
[1] "2.8"
[1] 1348
[1] TRUE
[1] "2.8"
[1] 1349
[1] TRUE
[1] "2.8"
[1] 1350
[1] TRUE
[1] "2.8"
[1] 1351
[1] TRUE
[1] "0.7"
[1] 1352
[1] TRUE
[1] "0.7"
[1] 1353
[1] TRUE
[1] "0.7"
[1] 1354
[1] TRUE
[1] "2.9"
[1] 1355
[1] TRUE
[1] "2.9"
[1] 1356
[1] TRUE
[1] "2.9"
[1] 1357
[1] TRUE
[1] "2.7"
[1] 1358
[1] TRUE
[1] "2.7"
[1] 1359
[1] TRUE
[1] "2.7"
[1] 1360
[1] TRUE
[1] "24.2"
[1] 1361
[1] TRUE
[1] "24.2"
[1] 1362
[1] TRUE
[1] "24.2"
[1] 1363
[1] TRUE
[1] "7.2"
[1] 1364
[1] TRUE
[1] "7.2"
[1] 1365
[1] TRUE
[1] "7.2"
[1] 1366
[1] TRUE
[1] "7.2"
[1] 1367
[1] TRUE
[1] "7.2"
[1] 1368
[1] TRUE
[1] "7.2"
[1] 1369
[1] TRUE
[1] "4.9000000000000004"
[1] 1370
[1] TRUE
[1] "4.9000000000000004"
[1] 1371
[1] TRUE
[1] "4.9000000000000004"
[1] 1372
[1] TRUE
[1] "1.3"
[1] 1373
[1] TRUE
[1] "1.3"
[1] 1374
[1] TRUE
[1] "1.3"
[1] 1375
[1] TRUE
[1] "1.3"
[1] 1376
[1] TRUE
[1] "1.7"
[1] 1377
[1] TRUE
[1] "1.7"
[1] 1378
[1] TRUE
[1] "1.2"
[1] 1379
[1] TRUE
[1] "1.2"
[1] 1380
[1] TRUE
[1] "1.8"
[1] 1381
[1] TRUE
[1] "1.8"
[1] 1382
[1] TRUE
[1] "1.8"
[1] 1383
[1] TRUE
[1] "1.8"
[1] 1384
[1] TRUE
[1] "2.8"
[1] 1385
[1] TRUE
[1] "2.8"
[1] 1386
[1] TRUE
[1] "6.2"
[1] 1387
[1] TRUE
[1] "6.2"
[1] 1388
[1] TRUE
[1] "6.2"
[1] 1389
[1] TRUE
[1] "6.2"
[1] 1390
[1] TRUE
[1] "7.2"
[1] 1391
[1] TRUE
[1] "7.2"
[1] 1392
[1] TRUE
[1] "3.4"
[1] 1393
[1] TRUE
[1] "3.4"
[1] 1394
[1] TRUE
[1] "0.2"
[1] 1395
[1] TRUE
[1] "0.2"
[1] 1396
[1] TRUE
[1] "0.2"
[1] 1397
[1] TRUE
[1] "0.2"
[1] 1398
[1] TRUE
[1] "15.2"
[1] 1399
[1] TRUE
[1] "15.2"
[1] 1400
[1] TRUE
[1] "1.4"
[1] 1401
[1] TRUE
[1] "1.4"
[1] 1402
[1] TRUE
[1] "1.4"
[1] 1403
[1] TRUE
[1] "1.4"
[1] 1404
[1] TRUE
[1] "1.4"
[1] 1405
[1] TRUE
[1] "1.4"
[1] 1406
[1] TRUE
[1] "17.100000000000001"
[1] 1407
[1] TRUE
[1] "17.100000000000001"
[1] 1408
[1] TRUE
[1] "18.600000000000001"
[1] 1409
[1] TRUE
[1] "18.600000000000001"
[1] 1410
[1] TRUE
[1] "18.600000000000001"
[1] 1411
[1] TRUE
[1] "18.600000000000001"
[1] 1412
[1] TRUE
[1] "23.8"
[1] 1413
[1] TRUE
[1] "23.8"
[1] 1414
[1] TRUE
[1] "0.8"
[1] 1415
[1] TRUE
[1] "0.8"
[1] 1416
[1] TRUE
[1] "0.8"
[1] 1417
[1] TRUE
[1] "0.8"
[1] 1418
[1] TRUE
[1] "0.8"
[1] 1419
[1] TRUE
[1] "0.8"
[1] 1420
[1] TRUE
[1] "10.199999999999999"
[1] 1421
[1] TRUE
[1] "10.199999999999999"
[1] 1422
[1] TRUE
[1] "10.199999999999999"
[1] 1423
[1] TRUE
[1] "10.199999999999999"
[1] 1424
[1] TRUE
[1] "13.4"
[1] 1425
[1] TRUE
[1] "13.4"
[1] 1426
[1] TRUE
[1] "0.5"
[1] 1427
[1] TRUE
[1] "0.5"
[1] 1428
[1] TRUE
[1] "0.5"
[1] 1429
[1] TRUE
[1] "0.5"
[1] 1430
[1] TRUE
[1] "8.3000000000000007"
[1] 1431
[1] TRUE
[1] "8.3000000000000007"
[1] 1432
[1] TRUE
[1] "8.3000000000000007"
[1] 1433
[1] TRUE
[1] "8.3000000000000007"
[1] 1434
[1] TRUE
[1] "10.1"
[1] 1435
[1] TRUE
[1] "10.1"
[1] 1436
[1] TRUE
[1] "6.6"
[1] 1437
[1] TRUE
[1] "6.6"
[1] 1438
[1] TRUE
[1] "6.6"
[1] 1439
[1] TRUE
[1] "6.6"
[1] 1440
[1] TRUE
[1] "7.7"
[1] 1441
[1] TRUE
[1] "7.7"
[1] 1442
[1] TRUE
[1] "7.2"
[1] 1443
[1] TRUE
[1] "7.2"
[1] 1444
[1] TRUE
[1] "12.8"
[1] 1445
[1] TRUE
[1] "12.8"
[1] 1446
[1] TRUE
[1] "12.8"
[1] 1447
[1] TRUE
[1] "12.8"
[1] 1448
[1] TRUE
[1] "15.8"
[1] 1449
[1] TRUE
[1] "15.8"
[1] 1450
[1] TRUE
[1] "7.7"
[1] 1451
[1] TRUE
[1] "7.7"
[1] 1452
[1] TRUE
[1] "7.7"
[1] 1453
[1] TRUE
[1] "7.7"
[1] 1454
[1] TRUE
[1] "12.0"
[1] 1455
[1] TRUE
[1] "12.0"
[1] 1456
[1] TRUE
[1] "4.0999999999999996"
[1] 1457
[1] TRUE
[1] "4.0999999999999996"
[1] 1458
[1] TRUE
[1] "4.0999999999999996"
[1] 1459
[1] TRUE
[1] "4.0999999999999996"
[1] 1460
[1] TRUE
[1] "4.7"
[1] 1461
[1] TRUE
[1] "4.7"
[1] 1462
[1] TRUE
[1] "5.0999999999999996"
[1] 1463
[1] TRUE
[1] "5.0999999999999996"
[1] 1464
[1] TRUE
[1] "7.9"
[1] 1465
[1] TRUE
[1] "7.9"
[1] 1466
[1] TRUE
[1] "15.6"
[1] 1467
[1] TRUE
[1] "15.6"
[1] 1468
[1] TRUE
[1] "8.5"
[1] 1469
[1] TRUE
[1] "8.5"
[1] 1470
[1] TRUE
[1] "16.100000000000001"
[1] 1471
[1] TRUE
[1] "16.100000000000001"
[1] 1472
[1] TRUE
[1] "16.100000000000001"
[1] 1473
[1] TRUE
[1] "16.100000000000001"
[1] 1474
[1] TRUE
[1] "20.0"
[1] 1475
[1] TRUE
[1] "20.0"
[1] 1476
[1] TRUE
[1] "14.2"
[1] 1477
[1] TRUE
[1] "14.2"
[1] 1478
[1] TRUE
[1] "14.2"
[1] 1479
[1] TRUE
[1] "14.2"
[1] 1480
[1] TRUE
[1] "15.8"
[1] 1481
[1] TRUE
[1] "15.8"
[1] 1482
[1] TRUE
[1] "4.5999999999999996"
[1] 1483
[1] TRUE
[1] "4.5999999999999996"
[1] 1484
[1] TRUE
[1] "4.5999999999999996"
[1] 1485
[1] TRUE
[1] "4.5999999999999996"
[1] 1486
[1] TRUE
[1] "4.5"
[1] 1487
[1] TRUE
[1] "4.5"
[1] 1488
[1] TRUE
[1] "4.5"
[1] 1489
[1] TRUE
[1] "4.5"
[1] 1490
[1] TRUE
[1] "6.0"
[1] 1491
[1] TRUE
[1] "6.0"
[1] 1492
[1] TRUE
[1] "5.5"
[1] 1493
[1] TRUE
[1] "5.5"
[1] 1494
[1] TRUE
[1] "5.5"
[1] 1495
[1] TRUE
[1] "12.5"
[1] 1496
[1] TRUE
[1] "12.5"
[1] 1497
[1] TRUE
[1] "12.5"
[1] 1498
[1] TRUE
[1] "12.5"
[1] 1499
[1] TRUE
[1] "16.7"
[1] 1500
[1] TRUE
[1] "16.7"
[1] 1501
[1] TRUE
[1] "16.8"
[1] 1502
[1] TRUE
[1] "16.8"
[1] 1503
[1] TRUE
[1] "16.8"
[1] 1504
[1] TRUE
[1] "16.8"
[1] 1505
[1] TRUE
[1] "16.8"
[1] 1506
[1] TRUE
[1] "16.8"
[1] 1507
[1] TRUE
[1] "22.6"
[1] 1508
[1] TRUE
[1] "22.6"
[1] 1509
[1] TRUE
[1] "22.6"
[1] 1510
[1] TRUE
[1] "22.4"
[1] 1511
[1] TRUE
[1] "22.4"
[1] 1512
[1] TRUE
[1] "22.4"
[1] 1513
[1] TRUE
[1] "25.1"
[1] 1514
[1] TRUE
[1] "25.1"
[1] 1515
[1] TRUE
[1] "25.1"
[1] 1516
[1] TRUE
[1] "5.0999999999999996"
[1] 1517
[1] TRUE
[1] "5.0999999999999996"
[1] 1518
[1] TRUE
[1] "5.0999999999999996"
[1] 1519
[1] TRUE
[1] "5.0999999999999996"
[1] 1520
[1] TRUE
[1] "5.0999999999999996"
[1] 1521
[1] TRUE
[1] "5.0999999999999996"
[1] 1522
[1] TRUE
[1] "5.2"
[1] 1523
[1] TRUE
[1] "5.2"
[1] 1524
[1] TRUE
[1] "5.2"
[1] 1525
[1] TRUE
[1] "6.6"
[1] 1526
[1] TRUE
[1] "6.6"
[1] 1527
[1] TRUE
[1] "6.6"
[1] 1528
[1] TRUE
[1] "5.0999999999999996"
[1] 1529
[1] TRUE
[1] "5.0999999999999996"
[1] 1530
[1] TRUE
[1] "5.0999999999999996"
[1] 1531
[1] TRUE
[1] "26.8"
[1] 1532
[1] TRUE
[1] "26.8"
[1] 1533
[1] TRUE
[1] "26.8"
[1] 1534
[1] TRUE
[1] "26.8"
[1] 1535
[1] TRUE
[1] "26.8"
[1] 1536
[1] TRUE
[1] "26.8"
[1] 1537
[1] TRUE
[1] "28.5"
[1] 1538
[1] TRUE
[1] "28.5"
[1] 1539
[1] TRUE
[1] "28.5"
[1] 1540
[1] TRUE
[1] "29.3"
[1] 1541
[1] TRUE
[1] "29.3"
[1] 1542
[1] TRUE
[1] "29.3"
[1] 1543
[1] TRUE
[1] "19.100000000000001"
[1] 1544
[1] TRUE
[1] "19.100000000000001"
[1] 1545
[1] TRUE
[1] "19.100000000000001"
[1] 1546
[1] TRUE
[1] "28.5"
[1] 1547
[1] TRUE
[1] "28.5"
[1] 1548
[1] TRUE
[1] "28.5"
[1] 1549
[1] TRUE
[1] "26.9"
[1] 1550
[1] TRUE
[1] "26.9"
[1] 1551
[1] TRUE
[1] "26.9"
[1] 1552
[1] TRUE
[1] "10.7"
[1] 1553
[1] TRUE
[1] "10.7"
[1] 1554
[1] TRUE
[1] "10.7"
[1] 1555
[1] TRUE
[1] "13.9"
[1] 1556
[1] TRUE
[1] "13.9"
[1] 1557
[1] TRUE
[1] "13.9"
[1] 1558
[1] TRUE
[1] "12.6"
[1] 1559
[1] TRUE
[1] "12.6"
[1] 1560
[1] TRUE
[1] "12.6"
[1] 1561
[1] TRUE
[1] "9.4"
[1] 1562
[1] TRUE
[1] "9.4"
[1] 1563
[1] TRUE
[1] "9.4"
[1] 1564
[1] TRUE
[1] "9.4"
[1] 1565
[1] TRUE
[1] "0.6"
[1] 1566
[1] TRUE
[1] "0.6"
[1] 1567
[1] TRUE
[1] "0.6"
[1] 1568
[1] TRUE
[1] "0.6"
[1] 1569
[1] TRUE
[1] "1.3"
[1] 1570
[1] TRUE
[1] "1.3"
[1] 1571
[1] TRUE
[1] "1.3"
[1] 1572
[1] TRUE
[1] "1.3"
[1] 1573
[1] TRUE
[1] "1.3"
[1] 1574
[1] TRUE
[1] "1.3"
[1] 1575
[1] TRUE
[1] "10.8"
[1] 1576
[1] TRUE
[1] "10.8"
[1] 1577
[1] TRUE
[1] "10.8"
[1] 1578
[1] TRUE
[1] "23.6"
[1] 1579
[1] TRUE
[1] "23.6"
[1] 1580
[1] TRUE
[1] "23.6"
[1] 1581
[1] TRUE
[1] "23.6"
[1] 1582
[1] TRUE
[1] "23.6"
[1] 1583
[1] TRUE
[1] "23.6"
[1] 1584
[1] TRUE
[1] "17.899999999999999"
[1] 1585
[1] TRUE
[1] "17.899999999999999"
[1] 1586
[1] TRUE
[1] "17.899999999999999"
[1] 1587
[1] TRUE
[1] "19.0"
[1] 1588
[1] TRUE
[1] "19.0"
[1] 1589
[1] TRUE
[1] "19.0"
[1] 1590
[1] TRUE
[1] "18.899999999999999"
[1] 1591
[1] TRUE
[1] "18.899999999999999"
[1] 1592
[1] TRUE
[1] "18.899999999999999"
[1] 1593
[1] TRUE
[1] "13.0"
[1] 1594
[1] TRUE
[1] "13.0"
[1] 1595
[1] TRUE
[1] "13.0"
[1] 1596
[1] TRUE
[1] "1.6"
[1] 1597
[1] TRUE
[1] "1.6"
[1] 1598
[1] TRUE
[1] "1.6"
[1] 1599
[1] TRUE
[1] "1.6"
[1] 1600
[1] TRUE
[1] "8.0"
[1] 1601
[1] TRUE
[1] "8.0"
[1] 1602
[1] TRUE
[1] "8.0"
[1] 1603
[1] TRUE
[1] "8.0"
[1] 1604
[1] TRUE
[1] "8.0"
[1] 1605
[1] TRUE
[1] "8.0"
[1] 1606
[1] TRUE
[1] "2.0"
[1] 1607
[1] TRUE
[1] "2.0"
[1] 1608
[1] TRUE
[1] "2.0"
[1] 1609
[1] TRUE
[1] "2.0"
[1] 1610
[1] TRUE
[1] "7.9"
[1] 1611
[1] TRUE
[1] "7.9"
[1] 1612
[1] TRUE
[1] "7.9"
[1] 1613
[1] TRUE
[1] "7.9"
[1] 1614
[1] TRUE
[1] "4.2"
[1] 1615
[1] TRUE
[1] "4.2"
[1] 1616
[1] TRUE
[1] "4.2"
[1] 1617
[1] TRUE
[1] "4.2"
[1] 1618
[1] TRUE
[1] "3.1"
[1] 1619
[1] TRUE
[1] "3.1"
[1] 1620
[1] TRUE
[1] "3.1"
[1] 1621
[1] TRUE
[1] "3.1"
[1] 1622
[1] TRUE
[1] "6.7"
[1] 1623
[1] TRUE
[1] "6.7"
[1] 1624
[1] TRUE
[1] "6.7"
[1] 1625
[1] TRUE
[1] "6.7"
[1] 1626
[1] TRUE
[1] "2.4"
[1] 1627
[1] TRUE
[1] "2.4"
[1] 1628
[1] TRUE
[1] "2.4"
[1] 1629
[1] TRUE
[1] "2.4"
[1] 1630
[1] TRUE
[1] "5.8"
[1] 1631
[1] TRUE
[1] "5.8"
[1] 1632
[1] TRUE
[1] "5.8"
[1] 1633
[1] TRUE
[1] "5.8"
[1] 1634
[1] TRUE
[1] "9.4"
[1] 1635
[1] TRUE
[1] "9.4"
[1] 1636
[1] TRUE
[1] "9.4"
[1] 1637
[1] TRUE
[1] "9.4"
[1] 1638
[1] TRUE
[1] "5.9"
[1] 1639
[1] TRUE
[1] "5.9"
[1] 1640
[1] TRUE
[1] "11.9"
[1] 1641
[1] TRUE
[1] "11.9"
[1] 1642
[1] TRUE
[1] "12.0"
[1] 1643
[1] TRUE
[1] "12.0"
[1] 1644
[1] TRUE
[1] "1.5"
[1] 1645
[1] TRUE
[1] "1.5"
[1] 1646
[1] TRUE
[1] "1.5"
[1] 1647
[1] TRUE
[1] "1.5"
[1] 1648
[1] TRUE
[1] "9.0"
[1] 1649
[1] TRUE
[1] "9.0"
[1] 1650
[1] TRUE
[1] "9.0"
[1] 1651
[1] TRUE
[1] "9.0"
[1] 1652
[1] TRUE
[1] "20.9"
[1] 1653
[1] TRUE
[1] "20.9"
[1] 1654
[1] TRUE
[1] "20.9"
[1] 1655
[1] TRUE
[1] "20.9"
[1] 1656
[1] TRUE
[1] "0.3"
[1] 1657
[1] TRUE
[1] "0.3"
[1] 1658
[1] TRUE
[1] "0.3"
[1] 1659
[1] TRUE
[1] "0.3"
[1] 1660
[1] TRUE
[1] "11.9"
[1] 1661
[1] TRUE
[1] "11.9"
[1] 1662
[1] TRUE
[1] "0.2"
[1] 1663
[1] TRUE
[1] "0.2"
[1] 1664
[1] TRUE
[1] "0.2"
[1] 1665
[1] TRUE
[1] "0.2"
[1] 1666
[1] TRUE
[1] "0.2"
[1] 1667
[1] TRUE
[1] "0.2"
[1] 1668
[1] TRUE
[1] "6.1"
[1] 1669
[1] TRUE
[1] "6.1"
[1] 1670
[1] TRUE
[1] "0.2"
[1] 1671
[1] TRUE
[1] "0.2"
[1] 1672
[1] TRUE
[1] "0.2"
[1] 1673
[1] TRUE
[1] "0.2"
[1] 1674
[1] TRUE
[1] "0.2"
[1] 1675
[1] TRUE
[1] "0.2"
[1] 1676
[1] TRUE
[1] "0.8"
[1] 1677
[1] TRUE
[1] "0.8"
[1] 1678
[1] TRUE
[1] "0.8"
[1] 1679
[1] TRUE
[1] "0.8"
[1] 1680
[1] TRUE
[1] "0.6"
[1] 1681
[1] TRUE
[1] "0.6"
[1] 1682
[1] TRUE
[1] "0.6"
[1] 1683
[1] TRUE
[1] "0.6"
[1] 1684
[1] TRUE
[1] "1.2"
[1] 1685
[1] TRUE
[1] "1.2"
[1] 1686
[1] TRUE
[1] "1.2"
[1] 1687
[1] TRUE
[1] "1.2"
[1] 1688
[1] TRUE
[1] "1.2"
[1] 1689
[1] TRUE
[1] "1.2"
[1] 1690
[1] TRUE
[1] "0.7"
[1] 1691
[1] TRUE
[1] "0.7"
[1] 1692
[1] TRUE
[1] "0.7"
[1] 1693
[1] TRUE
[1] "0.7"
[1] 1694
[1] TRUE
[1] "0.7"
[1] 1695
[1] TRUE
[1] "0.7"
[1] 1696
[1] TRUE
[1] "5.3"
[1] 1697
[1] TRUE
[1] "5.3"
[1] 1698
[1] TRUE
[1] "5.3"
[1] 1699
[1] TRUE
[1] "5.3"
[1] 1700
[1] TRUE
[1] "8.6"
[1] 1701
[1] TRUE
[1] "8.6"
[1] 1702
[1] TRUE
[1] "8.6"
[1] 1703
[1] TRUE
[1] "8.6"
[1] 1704
[1] TRUE
[1] "1.2"
[1] 1705
[1] TRUE
[1] "1.2"
[1] 1706
[1] TRUE
[1] "1.2"
[1] 1707
[1] TRUE
[1] "1.2"
[1] 1708
[1] TRUE
[1] "15.1"
[1] 1709
[1] TRUE
[1] "15.1"
[1] 1710
[1] TRUE
[1] "15.1"
[1] 1711
[1] TRUE
[1] "15.1"
[1] 1712
[1] TRUE
[1] "15.1"
[1] 1713
[1] TRUE
[1] "15.1"
[1] 1714
[1] TRUE
[1] "16.7"
[1] 1715
[1] TRUE
[1] "16.7"
[1] 1716
[1] TRUE
[1] "16.7"
[1] 1717
[1] TRUE
[1] "19.7"
[1] 1718
[1] TRUE
[1] "19.7"
[1] 1719
[1] TRUE
[1] "19.7"
[1] 1720
[1] TRUE
[1] "22.1"
[1] 1721
[1] TRUE
[1] "22.1"
[1] 1722
[1] TRUE
[1] "22.1"
[1] 1723
[1] TRUE
[1] "6.7"
[1] 1724
[1] TRUE
[1] "6.7"
[1] 1725
[1] TRUE
[1] "6.7"
[1] 1726
[1] TRUE
[1] "6.7"
[1] 1727
[1] TRUE
[1] "13.6"
[1] 1728
[1] TRUE
[1] "13.6"
[1] 1729
[1] TRUE
[1] "13.6"
[1] 1730
[1] TRUE
[1] "5.7"
[1] 1731
[1] TRUE
[1] "5.7"
[1] 1732
[1] TRUE
[1] "5.7"
[1] 1733
[1] TRUE
[1] "5.7"
[1] 1734
[1] TRUE
[1] "0.3"
[1] 1735
[1] TRUE
[1] "0.3"
[1] 1736
[1] TRUE
[1] "0.3"
[1] 1737
[1] TRUE
[1] "0.3"
[1] 1738
[1] TRUE
[1] "5.3"
[1] 1739
[1] TRUE
[1] "5.3"
[1] 1740
[1] TRUE
[1] "5.3"
[1] 1741
[1] TRUE
[1] "5.3"
[1] 1742
[1] TRUE
[1] "2.0"
[1] 1743
[1] TRUE
[1] "2.0"
[1] 1744
[1] TRUE
[1] "2.0"
[1] 1745
[1] TRUE
[1] "2.0"
[1] 1746
[1] TRUE
[1] "3.7"
[1] 1747
[1] TRUE
[1] "3.7"
[1] 1748
[1] TRUE
[1] "3.7"
[1] 1749
[1] TRUE
[1] "3.7"
[1] 1750
[1] TRUE
[1] "2.5"
[1] 1751
[1] TRUE
[1] "2.5"
[1] 1752
[1] TRUE
[1] "2.5"
[1] 1753
[1] TRUE
[1] "2.5"
[1] 1754
[1] TRUE
[1] "0.3"
[1] 1755
[1] TRUE
[1] "0.3"
[1] 1756
[1] TRUE
[1] "0.3"
[1] 1757
[1] TRUE
[1] "0.3"
[1] 1758
[1] TRUE
[1] "0.4"
[1] 1759
[1] TRUE
[1] "0.4"
[1] 1760
[1] TRUE
[1] "0.4"
[1] 1761
[1] TRUE
[1] "0.4"
[1] 1762
[1] TRUE
[1] "2.5"
[1] 1763
[1] TRUE
[1] "2.5"
[1] 1764
[1] TRUE
[1] "2.5"
[1] 1765
[1] TRUE
[1] "2.5"
[1] 1766
[1] TRUE
[1] "2.8"
[1] 1767
[1] TRUE
[1] "2.8"
[1] 1768
[1] TRUE
[1] "3.6"
[1] 1769
[1] TRUE
[1] "20.399999999999999"
[1] 1770
[1] TRUE
[1] "20.399999999999999"
[1] 1771
[1] TRUE
[1] "20.399999999999999"
[1] 1772
[1] TRUE
[1] "4.2"
[1] 1773
[1] TRUE
[1] "4.2"
[1] 1774
[1] TRUE
[1] "4.2"
[1] 1775
[1] TRUE
[1] "4.2"
[1] 1776
[1] TRUE
[1] "1.3"
[1] 1777
[1] TRUE
[1] "1.3"
[1] 1778
[1] TRUE
[1] "1.3"
[1] 1779
[1] TRUE
[1] "1.3"
[1] 1780
[1] TRUE
[1] "4.4000000000000004"
[1] 1781
[1] TRUE
[1] "4.4000000000000004"
[1] 1782
[1] TRUE
[1] "4.4000000000000004"
[1] 1783
[1] TRUE
[1] "4.4000000000000004"
[1] 1784
[1] TRUE
[1] "10.9"
[1] 1785
[1] TRUE
[1] "10.9"
[1] 1786
[1] TRUE
[1] "4.0999999999999996"
[1] 1787
[1] TRUE
[1] "4.0999999999999996"
[1] 1788
[1] TRUE
[1] "4.0999999999999996"
[1] 1789
[1] TRUE
[1] "4.0999999999999996"
[1] 1790
[1] TRUE
[1] "0.4"
[1] 1791
[1] TRUE
[1] "0.4"
[1] 1792
[1] TRUE
[1] "0.4"
[1] 1793
[1] TRUE
[1] "0.4"
[1] 1794
[1] TRUE
[1] "0.4"
[1] 1795
[1] TRUE
[1] "0.4"
[1] 1796
[1] TRUE
[1] "1.4"
[1] 1797
[1] TRUE
[1] "1.4"
[1] 1798
[1] TRUE
[1] "1.4"
[1] 1799
[1] TRUE
[1] "1.4"
[1] 1800
[1] TRUE
[1] "1.4"
[1] 1801
[1] TRUE
[1] "1.4"
[1] 1802
[1] TRUE
[1] "27.5"
[1] 1803
[1] TRUE
[1] "27.5"
[1] 1804
[1] TRUE
[1] "27.5"
[1] 1805
[1] TRUE
[1] "27.5"
[1] 1806
[1] TRUE
[1] "27.5"
[1] 1807
[1] TRUE
[1] "27.5"
[1] 1808
[1] TRUE
[1] "0.7"
[1] 1809
[1] TRUE
[1] "0.7"
[1] 1810
[1] TRUE
[1] "0.7"
[1] 1811
[1] TRUE
[1] "0.7"
[1] 1812
[1] TRUE
[1] "0.7"
[1] 1813
[1] TRUE
[1] "0.7"
[1] 1814
[1] TRUE
[1] "0.1"
[1] 1815
[1] TRUE
[1] "0.1"
[1] 1816
[1] TRUE
[1] "0.1"
[1] 1817
[1] TRUE
[1] "0.1"
[1] 1818
[1] TRUE
[1] "0.1"
[1] 1819
[1] TRUE
[1] "0.1"
[1] 1820
[1] TRUE
[1] "28.3"
[1] 1821
[1] TRUE
[1] "28.3"
[1] 1822
[1] TRUE
[1] "28.3"
[1] 1823
[1] TRUE
[1] "28.3"
[1] 1824
[1] TRUE
[1] "28.3"
[1] 1825
[1] TRUE
[1] "28.3"
[1] 1826
[1] TRUE
[1] "4.8"
[1] 1827
[1] TRUE
[1] "4.8"
[1] 1828
[1] TRUE
[1] "4.8"
[1] 1829
[1] TRUE
[1] "4.8"
[1] 1830
[1] TRUE
[1] "4.8"
[1] 1831
[1] TRUE
[1] "4.8"
[1] 1832
[1] TRUE
[1] "1.2"
[1] 1833
[1] TRUE
[1] "1.2"
[1] 1834
[1] TRUE
[1] "1.2"
[1] 1835
[1] TRUE
[1] "1.2"
[1] 1836
[1] TRUE
[1] "1.2"
[1] 1837
[1] TRUE
[1] "1.2"
[1] 1838
[1] TRUE
[1] "0.7"
[1] 1839
[1] TRUE
[1] "0.7"
[1] 1840
[1] TRUE
[1] "0.7"
[1] 1841
[1] TRUE
[1] "2.5"
[1] 1842
[1] TRUE
[1] "2.5"
[1] 1843
[1] TRUE
[1] "2.5"
[1] 1844
[1] TRUE
[1] "2.2999999999999998"
[1] 1845
[1] TRUE
[1] "2.2999999999999998"
[1] 1846
[1] TRUE
[1] "2.2999999999999998"
[1] 1847
[1] TRUE
[1] "21.7"
[1] 1848
[1] TRUE
[1] "21.7"
[1] 1849
[1] TRUE
[1] "21.7"
[1] 1850
[1] TRUE
[1] "23.6"
[1] 1851
[1] TRUE
[1] "23.6"
[1] 1852
[1] TRUE
[1] "23.6"
[1] 1853
[1] TRUE
[1] "22.9"
[1] 1854
[1] TRUE
[1] "22.9"
[1] 1855
[1] TRUE
[1] "22.9"
[1] 1856
[1] TRUE
[1] "22.9"
[1] 1857
[1] TRUE
[1] "10.9"
[1] 1858
[1] TRUE
[1] "10.9"
[1] 1859
[1] TRUE
[1] "10.9"
[1] 1860
[1] TRUE
[1] "10.9"
[1] 1861
[1] TRUE
[1] "10.9"
[1] 1862
[1] TRUE
[1] "10.9"
[1] 1863
[1] TRUE
[1] "3.0"
[1] 1864
[1] TRUE
[1] "3.0"
[1] 1865
[1] TRUE
[1] "3.0"
[1] 1866
[1] TRUE
[1] "3.0"
[1] 1867
[1] TRUE
[1] "0.3"
[1] 1868
[1] TRUE
[1] "0.3"
[1] 1869
[1] TRUE
[1] "0.3"
[1] 1870
[1] TRUE
[1] "0.3"
[1] 1871
[1] TRUE
[1] "12.6"
[1] 1872
[1] TRUE
[1] "12.6"
[1] 1873
[1] TRUE
[1] "12.6"
[1] 1874
[1] TRUE
[1] "12.6"
[1] 1875
[1] TRUE
[1] "8.4"
[1] 1876
[1] TRUE
[1] "8.4"
[1] 1877
[1] TRUE
[1] "4.5"
[1] 1878
[1] TRUE
[1] "4.5"
[1] 1879
[1] TRUE
[1] "4.5"
[1] 1880
[1] TRUE
[1] "4.5"
[1] 1881
[1] TRUE
[1] "3.5"
[1] 1882
[1] TRUE
[1] "3.5"
[1] 1883
[1] TRUE
[1] "3.5"
[1] 1884
[1] TRUE
[1] "3.5"
[1] 1885
[1] TRUE
[1] "0.6"
[1] 1886
[1] TRUE
[1] "0.6"
[1] 1887
[1] TRUE
[1] "0.6"
[1] 1888
[1] TRUE
[1] "0.6"
[1] 1889
[1] TRUE
[1] "21.8"
[1] 1890
[1] TRUE
[1] "21.8"
[1] 1891
[1] TRUE
[1] "21.8"
[1] 1892
[1] TRUE
[1] "21.8"
[1] 1893
[1] TRUE
[1] "4.3"
[1] 1894
[1] TRUE
[1] "4.3"
[1] 1895
[1] TRUE
[1] "4.3"
[1] 1896
[1] TRUE
[1] "4.3"
[1] 1897
[1] TRUE
[1] "1.7"
[1] 1898
[1] TRUE
[1] "1.7"
[1] 1899
[1] TRUE
[1] "1.7"
[1] 1900
[1] TRUE
[1] "1.7"
[1] 1901
[1] TRUE
[1] "5.5"
[1] 1902
[1] TRUE
[1] "5.5"
[1] 1903
[1] TRUE
[1] "5.0999999999999996"
[1] 1904
[1] TRUE
[1] "5.0999999999999996"
[1] 1905
[1] TRUE
[1] "0.3"
[1] 1906
[1] TRUE
[1] "0.3"
[1] 1907
[1] TRUE
[1] "0.6"
[1] 1908
[1] TRUE
[1] "0.6"
[1] 1909
[1] TRUE
[1] "0.3"
[1] 1910
[1] TRUE
[1] "0.3"
[1] 1911
[1] TRUE
[1] "2.2000000000000002"
[1] 1912
[1] TRUE
[1] "0.3"
[1] 1913
[1] TRUE
[1] "0.3"
[1] 1914
[1] TRUE
[1] "1.6"
[1] 1915
[1] TRUE
[1] "0.4"
[1] 1916
[1] TRUE
[1] "1.4"
[1] 1917
[1] TRUE
[1] "1.4"
[1] 1918
[1] TRUE
[1] "0.8"
[1] 1919
[1] TRUE
[1] "0.8"
[1] 1920
[1] TRUE
[1] "1.0"
[1] 1921
[1] TRUE
[1] "1.0"
[1] 1922
[1] TRUE
[1] "1.4"
[1] 1923
[1] TRUE
[1] "1.4"
[1] 1924
[1] TRUE
[1] "0.4"
[1] 1925
[1] TRUE
[1] "0.4"
[1] 1926
[1] TRUE
[1] "1.4"
[1] 1927
[1] TRUE
[1] "1.4"
[1] 1928
[1] TRUE
[1] "0.2"
[1] 1929
[1] TRUE
[1] "0.2"
[1] 1930
[1] TRUE
[1] "0.2"
[1] 1931
[1] TRUE
[1] "0.2"
[1] 1932
[1] TRUE
[1] "0.4"
[1] 1933
[1] TRUE
[1] "0.4"
[1] 1934
[1] TRUE
[1] "0.3"
[1] 1935
[1] TRUE
[1] "0.3"
[1] 1936
[1] TRUE
[1] "0.6"
[1] 1937
[1] TRUE
[1] "0.6"
[1] 1938
[1] TRUE
[1] "0.5"
[1] 1939
[1] TRUE
[1] "0.5"
[1] 1940
[1] TRUE
[1] "0.6"
[1] 1941
[1] TRUE
[1] "0.6"
[1] 1942
[1] TRUE
[1] "0.4"
[1] 1943
[1] TRUE
[1] "0.4"
[1] 1944
[1] TRUE
[1] "0.9"
[1] 1945
[1] TRUE
[1] "0.9"
[1] 1946
[1] TRUE
[1] "0.3"
[1] 1947
[1] TRUE
[1] "0.3"
[1] 1948
[1] TRUE
[1] "1.4"
[1] 1949
[1] TRUE
[1] "0.6"
[1] 1950
[1] TRUE
[1] "1.1000000000000001"
[1] 1951
[1] TRUE
[1] "1.1000000000000001"
[1] 1952
[1] TRUE
[1] "0.4"
[1] 1953
[1] TRUE
[1] "0.4"
[1] 1954
[1] TRUE
[1] "0.3"
[1] 1955
[1] TRUE
[1] "0.3"
[1] 1956
[1] TRUE
[1] "0.4"
[1] 1957
[1] TRUE
[1] "0.4"
[1] 1958
[1] TRUE
[1] "0.6"
[1] 1959
[1] TRUE
[1] "0.6"
[1] 1960
[1] TRUE
[1] "0.5"
[1] 1961
[1] TRUE
[1] "0.4"
[1] 1962
[1] TRUE
[1] "1.5"
[1] 1963
[1] TRUE
[1] "4.0"
[1] 1964
[1] TRUE
[1] "0.3"
[1] 1965
[1] TRUE
[1] "0.3"
[1] 1966
[1] TRUE
[1] "0.4"
[1] 1967
[1] TRUE
[1] "0.4"
[1] 1968
[1] TRUE
[1] "0.6"
[1] 1969
[1] TRUE
[1] "0.6"
[1] 1970
[1] TRUE
[1] "10.3"
[1] 1971
[1] TRUE
[1] "0.3"
[1] 1972
[1] TRUE
[1] "0.3"
[1] 1973
[1] TRUE
[1] "0.3"
[1] 1974
[1] TRUE
[1] "0.3"
[1] 1975
[1] TRUE
[1] "0.5"
[1] 1976
[1] TRUE
[1] "0.5"
[1] 1977
[1] TRUE
[1] "0.5"
[1] 1978
[1] TRUE
[1] "0.4"
[1] 1979
[1] TRUE
[1] "0.4"
[1] 1980
[1] TRUE
[1] "0.6"
[1] 1981
[1] TRUE
[1] "0.4"
[1] 1982
[1] TRUE
[1] "0.3"
[1] 1983
[1] TRUE
[1] "0.3"
[1] 1984
[1] TRUE
[1] "0.5"
[1] 1985
[1] TRUE
[1] "0.3"
[1] 1986
[1] TRUE
[1] "1.4"
[1] 1987
[1] TRUE
[1] "1.4"
[1] 1988
[1] TRUE
[1] "1.0"
[1] 1989
[1] TRUE
[1] "1.0"
[1] 1990
[1] TRUE
[1] "0.3"
[1] 1991
[1] TRUE
[1] "0.3"
[1] 1992
[1] TRUE
[1] "0.8"
[1] 1993
[1] TRUE
[1] "0.8"
[1] 1994
[1] TRUE
[1] "0.9"
[1] 1995
[1] TRUE
[1] "1.0"
[1] 1996
[1] TRUE
[1] "0.7"
[1] 1997
[1] TRUE
[1] "0.7"
[1] 1998
[1] TRUE
[1] "0.6"
[1] 1999
[1] TRUE
[1] "10.8"
[1] 2000
[1] TRUE
[1] "0.9"
[1] 2001
[1] TRUE
[1] "0.9"
[1] 2002
[1] TRUE
[1] "3.5"
[1] 2003
[1] TRUE
[1] "3.5"
[1] 2004
[1] TRUE
[1] "2.9"
[1] 2005
[1] TRUE
[1] "7.5"
[1] 2006
[1] TRUE
[1] "1.0"
[1] 2007
[1] TRUE
[1] "1.0"
[1] 2008
[1] TRUE
[1] "4.3"
[1] 2009
[1] TRUE
[1] "3.1"
[1] 2010
[1] TRUE
[1] "1.5"
[1] 2011
[1] TRUE
[1] "0.8"
[1] 2012
[1] TRUE
[1] "0.8"
[1] 2013
[1] TRUE
[1] "0.7"
[1] 2014
[1] TRUE
[1] "0.7"
[1] 2015
[1] TRUE
[1] "0.7"
[1] 2016
[1] TRUE
[1] "4.8"
[1] 2017
[1] TRUE
[1] "5.8"
[1] 2018
[1] TRUE
[1] "2.9"
[1] 2019
[1] TRUE
[1] "3.0"
[1] 2020
[1] TRUE
[1] "0.1"
[1] 2021
[1] TRUE
[1] "1.7"
[1] 2022
[1] TRUE
[1] "0.3"
[1] 2023
[1] TRUE
[1] "1.8"
[1] 2024
[1] TRUE
[1] "0.8"
[1] 2025
[1] TRUE
[1] "1.1000000000000001"
[1] 2026
[1] TRUE
[1] "0.4"
[1] 2027
[1] TRUE
[1] "31.4"
[1] 2028
[1] TRUE
[1] "68.8"
[1] 2029
[1] TRUE
[1] "0.9"
[1] 2030
[1] TRUE
[1] "0.6"
[1] 2031
[1] TRUE
[1] "0.6"
[1] 2032
[1] TRUE
[1] "0.6"
[1] 2033
[1] TRUE
[1] "0.6"
[1] 2034
[1] TRUE
[1] "0.7"
[1] 2035
[1] TRUE
[1] "0.7"
[1] 2036
[1] TRUE
[1] "0.8"
[1] 2037
[1] TRUE
[1] "0.8"
[1] 2038
[1] TRUE
[1] "0.7"
[1] 2039
[1] TRUE
[1] "0.7"
[1] 2040
[1] TRUE
[1] "4.8"
[1] 2041
[1] TRUE
[1] "4.8"
[1] 2042
[1] TRUE
[1] "11.7"
[1] 2043
[1] TRUE
[1] "11.7"
[1] 2044
[1] TRUE
[1] "11.7"
[1] 2045
[1] TRUE
[1] "11.7"
[1] 2046
[1] TRUE
[1] "12.6"
[1] 2047
[1] TRUE
[1] "12.6"
[1] 2048
[1] TRUE
[1] "13.1"
[1] 2049
[1] TRUE
[1] "13.1"
[1] 2050
[1] TRUE
[1] "14"
[1] 2051
[1] TRUE
[1] "14"
[1] 2052
[1] TRUE
[1] "4.3"
[1] 2053
[1] TRUE
[1] "4.3"
[1] 2054
[1] TRUE
[1] "4.3"
[1] 2055
[1] TRUE
[1] "4.3"
[1] 2056
[1] TRUE
[1] "5.2"
[1] 2057
[1] TRUE
[1] "5.2"
[1] 2058
[1] TRUE
[1] "5.6"
[1] 2059
[1] TRUE
[1] "5.6"
[1] 2060
[1] TRUE
[1] "5.2"
[1] 2061
[1] TRUE
[1] "5.2"
[1] 2062
[1] TRUE
[1] "1"
[1] 2063
[1] TRUE
[1] "1"
[1] 2064
[1] TRUE
[1] "1"
[1] 2065
[1] TRUE
[1] "1"
[1] 2066
[1] TRUE
[1] "1.2"
[1] 2067
[1] TRUE
[1] "1.2"
[1] 2068
[1] TRUE
[1] "1.3"
[1] 2069
[1] TRUE
[1] "1.3"
[1] 2070
[1] TRUE
[1] "1.2"
[1] 2071
[1] TRUE
[1] "1.2"
[1] 2072
[1] TRUE
[1] "3.5"
[1] 2073
[1] TRUE
[1] "3.5"
[1] 2074
[1] TRUE
[1] "3.5"
[1] 2075
[1] TRUE
[1] "3.5"
[1] 2076
[1] TRUE
[1] "4.2"
[1] 2077
[1] TRUE
[1] "4.2"
[1] 2078
[1] TRUE
[1] "4.5"
[1] 2079
[1] TRUE
[1] "4.5"
[1] 2080
[1] TRUE
[1] "4.2"
[1] 2081
[1] TRUE
[1] "4.2"
[1] 2082
[1] TRUE
[1] "5.9"
[1] 2083
[1] TRUE
[1] "5.9"
[1] 2084
[1] TRUE
[1] "5.9"
[1] 2085
[1] TRUE
[1] "5.9"
[1] 2086
[1] TRUE
[1] "5.9"
[1] 2087
[1] TRUE
[1] "5.9"
[1] 2088
[1] TRUE
[1] "0.9"
[1] 2089
[1] TRUE
[1] "0.9"
[1] 2090
[1] TRUE
[1] "0.9"
[1] 2091
[1] TRUE
[1] "0.9"
[1] 2092
[1] TRUE
[1] "1.5"
[1] 2093
[1] TRUE
[1] "1.5"
[1] 2094
[1] TRUE
[1] "1.5"
[1] 2095
[1] TRUE
[1] "1.5"
[1] 2096
[1] TRUE
[1] "1.1"
[1] 2097
[1] TRUE
[1] "1.1"
[1] 2098
[1] TRUE
[1] "1.3"
[1] 2099
[1] TRUE
[1] "1.3"
[1] 2100
[1] TRUE
[1] "7.4"
[1] 2101
[1] TRUE
[1] "7.4"
[1] 2102
[1] TRUE
[1] "7.4"
[1] 2103
[1] TRUE
[1] "7.4"
[1] 2104
[1] TRUE
[1] "7.4"
[1] 2105
[1] TRUE
[1] "7.4"
[1] 2106
[1] TRUE
[1] "7.4"
[1] 2107
[1] TRUE
[1] "7.4"
[1] 2108
[1] TRUE
[1] "7.4"
[1] 2109
[1] TRUE
[1] "7.5"
[1] 2110
[1] TRUE
[1] "7.5"
[1] 2111
[1] TRUE
[1] "7.5"
[1] 2112
[1] TRUE
[1] "8.7"
[1] 2113
[1] TRUE
[1] "8.7"
[1] 2114
[1] TRUE
[1] "8.7"
[1] 2115
[1] TRUE
[1] "0.8"
[1] 2116
[1] TRUE
[1] "0.8"
[1] 2117
[1] TRUE
[1] "0.8"
[1] 2118
[1] TRUE
[1] "0.8"
[1] 2119
[1] TRUE
[1] "1"
[1] 2120
[1] TRUE
[1] "1"
[1] 2121
[1] TRUE
[1] "1.1"
[1] 2122
[1] TRUE
[1] "1.1"
[1] 2123
[1] TRUE
[1] "1"
[1] 2124
[1] TRUE
[1] "1"
[1] 2125
[1] TRUE
[1] "2"
[1] 2126
[1] TRUE
[1] "2"
[1] 2127
[1] TRUE
[1] "2"
[1] 2128
[1] TRUE
[1] "2"
[1] 2129
[1] TRUE
[1] "2"
[1] 2130
[1] TRUE
[1] "2"
[1] 2131
[1] TRUE
[1] "2.5"
[1] 2132
[1] TRUE
[1] "2.5"
[1] 2133
[1] TRUE
[1] "2.5"
[1] 2134
[1] TRUE
[1] "2.7"
[1] 2135
[1] TRUE
[1] "2.7"
[1] 2136
[1] TRUE
[1] "2.7"
[1] 2137
[1] TRUE
[1] "2.5"
[1] 2138
[1] TRUE
[1] "2.5"
[1] 2139
[1] TRUE
[1] "2.5"
[1] 2140
[1] TRUE
[1] "100"
[1] 2141
[1] TRUE
[1] "100"
[1] 2142
[1] TRUE
[1] "100"
[1] 2143
[1] TRUE
[1] "100"
[1] 2144
[1] TRUE
[1] "100"
[1] 2145
[1] TRUE
[1] "100"
[1] 2146
[1] TRUE
[1] "100"
[1] 2147
[1] TRUE
[1] "100"
[1] 2148
[1] "11"
[1] 2149
[1] "11"
[1] 2150
[1] "0.2"
[1] 2151
[1] "0.2"
[1] 2152
[1] "2.6"
[1] 2153
[1] "2.6"
[1] 2154
[1] "0.2"
[1] 2155
[1] "0.2"
[1] 2156
[1] "3.2"
[1] 2157
[1] "3.2"
[1] 2158
[1] "0.6"
[1] 2159
[1] "6.1"
[1] 2160
[1] "6.1"
[1] 2161
[1] "11.5"
[1] 2162
[1] "11.5"
[1] 2163
[1] "14.7"
[1] 2164
[1] "0.2"
[1] 2165
[1] "0.2"
[1] 2166
[1] "0.2"
[1] 2167
[1] "0.2"
[1] 2168
[1] "5.4"
[1] 2169
[1] "5.4"
[1] 2170
[1] "24.1"
[1] 2171
[1] "0.3"
[1] 2172
[1] "0.3"
[1] 2173
[1] "0.6"
[1] 2174
[1] "0.6"
[1] 2175
[1] "25"
[1] 2176
[1] "25"
[1] 2177
[1] "14"
[1] 2178
[1] "14"
[1] 2179
[1] "9"
[1] 2180
[1] "2.5"
[1] 2181
[1] "2.5"
[1] 2182
[1] "1.1"
[1] 2183
[1] "1.1"
[1] 2184
[1] "0.3"
[1] 2185
[1] "0.3"
[1] 2186
[1] "0.3"
[1] 2187
[1] "1"
[1] 2188
[1] "1"
[1] 2189
[1] "2.8"
[1] 2190
[1] "2.8"
[1] 2191
[1] "2.8"
[1] 2192
[1] "3.3"
[1] 2193
[1] "3.3"
[1] 2194
[1] "0.6"
[1] 2195
[1] "0.6"
[1] 2196
[1] "32.5"
[1] 2197
[1] "32.5"
[1] 2198
[1] "30.5"
[1] 2199
[1] "2.6"
[1] 2200
[1] "1.4"
[1] 2201
[1] "1.4"
[1] 2202
[1] "0.6"
[1] 2203
[1] "1.8"
[1] 2204
[1] "0.8"
[1] 2205
[1] "2.4"
[1] 2206
[1] "2.4"
[1] 2207
[1] "4.4"
[1] 2208
[1] "2.8"
[1] 2209
[1] "0.9"
[1] 2210
[1] "1.4"
[1] 2211
[1] "13.1"
[1] 2212
[1] "2.3"
[1] 2213
[1] "0.6"
[1] 2214
[1] "16"
[1] 2215
[1] "5.5"
[1] 2216
[1] "1.8"
[1] 2217
[1] "20.5"
[1] 2218
[1] "0.3"
[1] 2219
[1] "1.9"
[1] 2220
[1] "0.4"
[1] 2221
[1] "18.9"
[1] 2222
[1] "1"
[1] 2223
[1] "0"
[1] 2224
[1] "0"
[1] 2225
[1] "2.4"
[1] 2226
[1] "2.4"
[1] 2227
[1] "0.3"
[1] 2228
[1] "0.3"
[1] 2229
[1] "7.1"
[1] 2230
[1] "7.1"
[1] 2231
[1] "0.5"
[1] 2232
[1] "0.5"
[1] 2233
[1] "5.2"
[1] 2234
[1] "5.2"
[1] 2235
[1] "1.3"
[1] 2236
[1] "12.8"
[1] 2237
[1] "12.9"
[1] 2238
[1] "6.8"
[1] 2239
[1] "4.3"
[1] 2240
[1] "10"
[1] 2241
[1] "10.1"
[1] 2242
[1] "0.4"
[1] 2243
[1] "0.1"
[1] 2244
[1] "0.1"
[1] 2245
[1] "11.4"
[1] 2246
[1] "2.8"
[1] 2247
[1] "6.5"
[1] 2248
[1] "13.7"
[1] 2249
[1] "5"
[1] 2250
[1] "4.5"
[1] 2251
[1] "3.8"
[1] 2252
[1] "6"
[1] 2253
[1] "10.2"
[1] 2254
[1] "3.8"
[1] 2255
[1] "6.7"
[1] 2256
[1] "6"
[1] 2257
[1] "0.2"
[1] 2258
[1] "8.1"
[1] 2259
[1] "1.2"
[1] 2260
[1] "9.2"
[1] 2261
[1] "1.4"
[1] 2262
[1] "6.9"
[1] 2263
[1] "1.7"
[1] 2264
[1] "1.7"
[1] 2265
[1] "0.8"
[1] 2266
[1] "3"
[1] 2267
[1] "9.2"
[1] 2268
[1] "14.4"
[1] 2269
[1] "15.2"
[1] 2270
[1] "17.3"
[1] 2271
[1] "12.4"
[1] 2272
[1] "16.4"
[1] 2273
[1] "13.6"
[1] 2274
[1] "20.4"
[1] 2275
[1] "5.6"
[1] 2276
[1] "7.2"
[1] 2277
[1] "14.2"
[1] 2278
[1] "8.2"
[1] 2279
[1] "13.5"
[1] 2280
[1] "11.4"
[1] 2281
[1] "21.9"
[1] 2282
[1] "13.6"
[1] 2283
[1] "10.6"
[1] 2284
[1] "7"
[1] 2285
[1] "2.7"
[1] 2286
[1] "1.9"
[1] 2287
[1] "1.1"
[1] 2288
[1] "2"
[1] 2289
[1] "2.9"
[1] 2290
[1] "1"
[1] 2291
[1] "16"
[1] 2292
[1] "18.8"
[1] 2293
[1] "2.5"
[1] 2294
[1] "21.2"
[1] 2295
[1] "13.3"
[1] 2296
[1] "5.1"
[1] 2297
[1] "14.7"
[1] 2298
[1] "20.9"
[1] 2299
[1] "1"
[1] 2300
[1] "1"
[1] 2301
[1] "19.4"
[1] 2302
[1] "11.9"
[1] 2303
[1] "16.6"
[1] 2304
[1] "16"
[1] 2305
[1] "4.3"
[1] 2306
[1] "1"
[1] 2307
[1] "5.1"
[1] 2308
[1] "4.3"
[1] 2309
[1] "17.7"
[1] 2310
[1] "19.8"
[1] 2311
[1] "6.1"
[1] 2312
[1] "6"
[1] 2313
[1] "0.5"
[1] 2314
[1] "0.5"
[1] 2315
[1] "7.1"
[1] 2316
[1] "8"
[1] 2317
[1] "7.6"
[1] 2318
[1] "1.4"
[1] 2319
[1] "1.4"
[1] 2320
[1] "0.4"
[1] 2321
[1] "23"
[1] 2322
[1] TRUE
[1] "100"
[1] 2323
[1] TRUE
[1] "100"
[1] 2324
[1] TRUE
[1] "100"
[1] 2325
[1] TRUE
[1] "100"
[1] 2326
[1] TRUE
[1] "100"
[1] 2327
[1] TRUE
[1] "100"
[1] 2328
[1] TRUE
[1] "100"
[1] 2329
[1] TRUE
[1] "100"
[1] 2330
[1] TRUE
[1] "3.23"
[1] 2331
[1] TRUE
[1] "3.23"
[1] 2332
[1] TRUE
[1] "3.23"
[1] 2333
[1] TRUE
[1] "3.23"
[1] 2334
[1] TRUE
[1] "0.9"
[1] 2335
[1] TRUE
[1] "0.9"
[1] 2336
[1] TRUE
[1] "5.6"
[1] 2337
[1] TRUE
[1] "5.6"
[1] 2338
[1] TRUE
[1] "0.7"
[1] 2339
[1] TRUE
[1] "0.7"
[1] 2340
[1] TRUE
[1] "0.7"
[1] 2341
[1] TRUE
[1] "1"
[1] 2342
[1] TRUE
[1] "1"
[1] 2343
[1] TRUE
[1] "1"
[1] 2344
[1] TRUE
[1] "1"
[1] 2345
[1] TRUE
[1] "1"
[1] 2346
[1] TRUE
[1] "1"
[1] 2347
[1] TRUE
[1] "7"
[1] 2348
[1] TRUE
[1] "7"
[1] 2349
[1] TRUE
[1] "7"
[1] 2350
[1] TRUE
[1] "1.1000000000000001"
[1] 2351
[1] TRUE
[1] "1.1000000000000001"
[1] 2352
[1] TRUE
[1] "1.1000000000000001"
[1] 2353
[1] TRUE
[1] "0.7"
[1] 2354
[1] TRUE
[1] "0.7"
[1] 2355
[1] TRUE
[1] "0.7"
[1] 2356
[1] TRUE
[1] "7.6"
[1] 2357
[1] TRUE
[1] "7.6"
[1] 2358
[1] TRUE
[1] "7.6"
[1] 2359
[1] TRUE
[1] "21.3"
[1] 2360
[1] TRUE
[1] "21.3"
[1] 2361
[1] TRUE
[1] "21.3"
[1] 2362
[1] TRUE
[1] "1.2"
[1] 2363
[1] TRUE
[1] "1.2"
[1] 2364
[1] TRUE
[1] "5.47"
[1] 2365
[1] TRUE
[1] "5.47"
[1] 2366
[1] TRUE
[1] "1.5"
[1] 2367
[1] TRUE
[1] "1.5"
[1] 2368
[1] TRUE
[1] "2.19"
[1] 2369
[1] TRUE
[1] "2.19"
[1] 2370
[1] TRUE
[1] "21.2"
[1] 2371
[1] TRUE
[1] "21.2"
[1] 2372
[1] TRUE
[1] "21.2"
[1] 2373
[1] TRUE
[1] "21.2"
[1] 2374
[1] TRUE
[1] "24.15"
[1] 2375
[1] TRUE
[1] "24.15"
[1] 2376
[1] TRUE
[1] "25.93"
[1] 2377
[1] TRUE
[1] "25.93"
[1] 2378
[1] TRUE
[1] "4.0999999999999996"
[1] 2379
[1] TRUE
[1] "4.0999999999999996"
[1] 2380
[1] TRUE
[1] "4.0999999999999996"
[1] 2381
[1] TRUE
[1] "4.0999999999999996"
[1] 2382
[1] TRUE
[1] "4.0999999999999996"
[1] 2383
[1] TRUE
[1] "4.0999999999999996"
[1] 2384
[1] TRUE
[1] "25.78"
[1] 2385
[1] TRUE
[1] "25.78"
[1] 2386
[1] TRUE
[1] "17.8"
[1] 2387
[1] TRUE
[1] "17.8"
[1] 2388
[1] TRUE
[1] "17.8"
[1] 2389
[1] TRUE
[1] "18.899999999999999"
[1] 2390
[1] TRUE
[1] "18.899999999999999"
[1] 2391
[1] TRUE
[1] "18.899999999999999"
[1] 2392
[1] TRUE
[1] "18.350000000000001"
[1] 2393
[1] TRUE
[1] "18.350000000000001"
[1] 2394
[1] TRUE
[1] "18.350000000000001"
[1] 2395
[1] TRUE
[1] "6"
[1] 2396
[1] TRUE
[1] "6"
[1] 2397
[1] TRUE
[1] "9.1999999999999993"
[1] 2398
[1] TRUE
[1] "9.1999999999999993"
[1] 2399
[1] TRUE
[1] "12.23"
[1] 2400
[1] TRUE
[1] "12.23"
[1] 2401
[1] TRUE
[1] "12.23"
[1] 2402
[1] TRUE
[1] "9.51"
[1] 2403
[1] TRUE
[1] "9.51"
[1] 2404
[1] TRUE
[1] "9.51"
[1] 2405
[1] TRUE
[1] "10.76"
[1] 2406
[1] TRUE
[1] "10.76"
[1] 2407
[1] TRUE
[1] "10.76"
[1] 2408
[1] TRUE
[1] "22.35"
[1] 2409
[1] TRUE
[1] "22.35"
[1] 2410
[1] TRUE
[1] "22.35"
[1] 2411
[1] TRUE
[1] "2.94"
[1] 2412
[1] TRUE
[1] "2.94"
[1] 2413
[1] TRUE
[1] "2.94"
[1] 2414
[1] TRUE
[1] "2.94"
[1] 2415
[1] TRUE
[1] "2.94"
[1] 2416
[1] TRUE
[1] "2.94"
[1] 2417
[1] TRUE
[1] "13.47"
[1] 2418
[1] TRUE
[1] "13.47"
[1] 2419
[1] TRUE
[1] "13.47"
[1] 2420
[1] TRUE
[1] "7.44"
[1] 2421
[1] TRUE
[1] "7.44"
[1] 2422
[1] TRUE
[1] "7.44"
[1] 2423
[1] TRUE
[1] "8.2100000000000009"
[1] 2424
[1] TRUE
[1] "8.2100000000000009"
[1] 2425
[1] TRUE
[1] "8.2100000000000009"
[1] 2426
[1] TRUE
[1] "9.8000000000000007"
[1] 2427
[1] TRUE
[1] "9.8000000000000007"
[1] 2428
[1] TRUE
[1] "9.8000000000000007"
[1] 2429
[1] TRUE
[1] "9.8000000000000007"
[1] 2430
[1] TRUE
[1] "9.8000000000000007"
[1] 2431
[1] TRUE
[1] "9.8000000000000007"
[1] 2432
[1] TRUE
[1] "7.6"
[1] 2433
[1] TRUE
[1] "7.6"
[1] 2434
[1] TRUE
[1] "7.6"
[1] 2435
[1] TRUE
[1] "7.6"
[1] 2436
[1] TRUE
[1] "0.6"
[1] 2437
[1] TRUE
[1] "0.6"
[1] 2438
[1] TRUE
[1] "0.6"
[1] 2439
[1] TRUE
[1] "0.6"
[1] 2440
[1] TRUE
[1] "1.6"
[1] 2441
[1] TRUE
[1] "1.6"
[1] 2442
[1] TRUE
[1] "1.6"
[1] 2443
[1] TRUE
[1] "1.6"
[1] 2444
[1] TRUE
[1] "1.1499999999999999"
[1] 2445
[1] TRUE
[1] "1.1499999999999999"
[1] 2446
[1] TRUE
[1] "1.1499999999999999"
[1] 2447
[1] TRUE
[1] "1.1499999999999999"
[1] 2448
[1] TRUE
[1] "3.4"
[1] 2449
[1] TRUE
[1] "3.4"
[1] 2450
[1] TRUE
[1] "3.4"
[1] 2451
[1] TRUE
[1] "3.4"
[1] 2452
[1] TRUE
[1] "0.8"
[1] 2453
[1] TRUE
[1] "0.8"
[1] 2454
[1] TRUE
[1] "0.8"
[1] 2455
[1] TRUE
[1] "0.8"
[1] 2456
[1] TRUE
[1] "4.9000000000000004"
[1] 2457
[1] TRUE
[1] "4.9000000000000004"
[1] 2458
[1] TRUE
[1] "4.9000000000000004"
[1] 2459
[1] TRUE
[1] "4.9000000000000004"
[1] 2460
[1] TRUE
[1] "4.9000000000000004"
[1] 2461
[1] TRUE
[1] "4.9000000000000004"
[1] 2462
[1] TRUE
[1] "1.2"
[1] 2463
[1] TRUE
[1] "1.2"
[1] 2464
[1] TRUE
[1] "1.2"
[1] 2465
[1] TRUE
[1] "1.2"
[1] 2466
[1] TRUE
[1] "0.78"
[1] 2467
[1] TRUE
[1] "0.78"
[1] 2468
[1] TRUE
[1] "0.78"
[1] 2469
[1] TRUE
[1] "0.78"
[1] 2470
[1] TRUE
[1] "1.2"
[1] 2471
[1] TRUE
[1] "1.2"
[1] 2472
[1] TRUE
[1] "1.2"
[1] 2473
[1] TRUE
[1] "1.2"
[1] 2474
[1] TRUE
[1] "1.2"
[1] 2475
[1] TRUE
[1] "1.2"
[1] 2476
[1] TRUE
[1] "0.97"
[1] 2477
[1] TRUE
[1] "0.97"
[1] 2478
[1] TRUE
[1] "0.97"
[1] 2479
[1] TRUE
[1] "0.97"
[1] 2480
[1] TRUE
[1] "0.97"
[1] 2481
[1] TRUE
[1] "0.97"
[1] 2482
[1] TRUE
[1] "1.2"
[1] 2483
[1] TRUE
[1] "1.2"
[1] 2484
[1] TRUE
[1] "1.2"
[1] 2485
[1] TRUE
[1] "1.2"
[1] 2486
[1] TRUE
[1] "2.1800000000000002"
[1] 2487
[1] TRUE
[1] "2.1800000000000002"
[1] 2488
[1] TRUE
[1] "2.1800000000000002"
[1] 2489
[1] TRUE
[1] "2.1800000000000002"
[1] 2490
[1] TRUE
[1] "2.1800000000000002"
[1] 2491
[1] TRUE
[1] "2.1800000000000002"
[1] 2492
[1] TRUE
[1] "11"
[1] 2493
[1] TRUE
[1] "11"
[1] 2494
[1] TRUE
[1] "11"
[1] 2495
[1] TRUE
[1] "11"
[1] 2496
[1] TRUE
[1] "11"
[1] 2497
[1] TRUE
[1] "11"
[1] 2498
[1] TRUE
[1] "0.8"
[1] 2499
[1] TRUE
[1] "0.8"
[1] 2500
[1] TRUE
[1] "0.8"
[1] 2501
[1] TRUE
[1] "0.8"
[1] 2502
[1] TRUE
[1] "1.21"
[1] 2503
[1] TRUE
[1] "1.21"
[1] 2504
[1] TRUE
[1] "1.21"
[1] 2505
[1] TRUE
[1] "1.21"
[1] 2506
[1] TRUE
[1] "0.64"
[1] 2507
[1] TRUE
[1] "0.64"
[1] 2508
[1] TRUE
[1] "0.64"
[1] 2509
[1] TRUE
[1] "0.64"
[1] 2510
[1] TRUE
[1] "0.42"
[1] 2511
[1] TRUE
[1] "0.42"
[1] 2512
[1] TRUE
[1] "0.42"
[1] 2513
[1] TRUE
[1] "0.42"
[1] 2514
[1] TRUE
[1] "1.06"
[1] 2515
[1] TRUE
[1] "1.06"
[1] 2516
[1] TRUE
[1] "1.06"
[1] 2517
[1] TRUE
[1] "1.06"
[1] 2518
[1] TRUE
[1] "2.12"
[1] 2519
[1] TRUE
[1] "2.12"
[1] 2520
[1] TRUE
[1] "3.12"
[1] 2521
[1] TRUE
[1] "3.12"
[1] 2522
[1] TRUE
[1] "0.44"
[1] 2523
[1] TRUE
[1] "0.44"
[1] 2524
[1] TRUE
[1] "0.44"
[1] 2525
[1] TRUE
[1] "0.44"
[1] 2526
[1] TRUE
[1] "3.03"
[1] 2527
[1] TRUE
[1] "3.03"
[1] 2528
[1] TRUE
[1] "3.03"
[1] 2529
[1] TRUE
[1] "5.63"
[1] 2530
[1] TRUE
[1] "5.63"
[1] 2531
[1] TRUE
[1] "5.63"
[1] 2532
[1] TRUE
[1] "5.63"
[1] 2533
[1] TRUE
[1] "2.5"
[1] 2534
[1] TRUE
[1] "2.5"
[1] 2535
[1] TRUE
[1] "1.6"
[1] 2536
[1] TRUE
[1] "1.6"
[1] 2537
[1] TRUE
[1] "3.63"
[1] 2538
[1] TRUE
[1] "3.63"
[1] 2539
[1] TRUE
[1] "3.63"
[1] 2540
[1] TRUE
[1] "3.63"
[1] 2541
[1] TRUE
[1] "2.8"
[1] 2542
[1] TRUE
[1] "2.8"
[1] 2543
[1] TRUE
[1] "2.8"
[1] 2544
[1] TRUE
[1] "2.8"
[1] 2545
[1] TRUE
[1] "0.81"
[1] 2546
[1] TRUE
[1] "0.81"
[1] 2547
[1] TRUE
[1] "0.81"
[1] 2548
[1] TRUE
[1] "0.81"
[1] 2549
[1] TRUE
[1] "2.91"
[1] 2550
[1] TRUE
[1] "2.91"
[1] 2551
[1] TRUE
[1] "2.91"
[1] 2552
[1] TRUE
[1] "1.2"
[1] 2553
[1] TRUE
[1] "1.2"
[1] 2554
[1] TRUE
[1] "1.2"
[1] 2555
[1] TRUE
[1] "1.2"
[1] 2556
[1] TRUE
[1] "2.5"
[1] 2557
[1] TRUE
[1] "2.5"
[1] 2558
[1] TRUE
[1] "2.5"
[1] 2559
[1] TRUE
[1] "2.5"
[1] 2560
[1] TRUE
[1] "12.05"
[1] 2561
[1] TRUE
[1] "12.05"
[1] 2562
[1] TRUE
[1] "12.05"
[1] 2563
[1] TRUE
[1] "12.05"
[1] 2564
[1] TRUE
[1] "1.5"
[1] 2565
[1] TRUE
[1] "1.5"
[1] 2566
[1] TRUE
[1] "1.5"
[1] 2567
[1] TRUE
[1] "1.5"
[1] 2568
[1] TRUE
[1] "2.98"
[1] 2569
[1] TRUE
[1] "2.98"
[1] 2570
[1] TRUE
[1] "2.98"
[1] 2571
[1] TRUE
[1] "0.6"
[1] 2572
[1] TRUE
[1] "0.6"
[1] 2573
[1] TRUE
[1] "0.95"
[1] 2574
[1] TRUE
[1] "0.95"
[1] 2575
[1] TRUE
[1] "0.95"
[1] 2576
[1] TRUE
[1] "0.95"
[1] 2577
[1] TRUE
[1] "1.22"
[1] 2578
[1] TRUE
[1] "1.22"
[1] 2579
[1] TRUE
[1] "1.22"
[1] 2580
[1] TRUE
[1] "1.22"
[1] 2581
[1] TRUE
[1] "1.22"
[1] 2582
[1] TRUE
[1] "1.22"
[1] 2583
[1] TRUE
[1] "0.69"
[1] 2584
[1] TRUE
[1] "0.69"
[1] 2585
[1] TRUE
[1] "0.69"
[1] 2586
[1] TRUE
[1] "0.69"
[1] 2587
[1] TRUE
[1] "1.65"
[1] 2588
[1] TRUE
[1] "1.65"
[1] 2589
[1] TRUE
[1] "1.65"
[1] 2590
[1] TRUE
[1] "1.65"
[1] 2591
[1] TRUE
[1] "7.19"
[1] 2592
[1] TRUE
[1] "7.19"
[1] 2593
[1] TRUE
[1] "7.19"
[1] 2594
[1] TRUE
[1] "0.62"
[1] 2595
[1] TRUE
[1] "0.62"
[1] 2596
[1] TRUE
[1] "0.62"
[1] 2597
[1] TRUE
[1] "0.62"
[1] 2598
[1] TRUE
[1] "1.5"
[1] 2599
[1] TRUE
[1] "1.5"
[1] 2600
[1] TRUE
[1] "1.5"
[1] 2601
[1] TRUE
[1] "1.5"
[1] 2602
[1] TRUE
[1] "0.57999999999999996"
[1] 2603
[1] TRUE
[1] "0.57999999999999996"
[1] 2604
[1] TRUE
[1] "0.57999999999999996"
[1] 2605
[1] TRUE
[1] "0.57999999999999996"
[1] 2606
[1] TRUE
[1] "11.98"
[1] 2607
[1] TRUE
[1] "11.98"
[1] 2608
[1] TRUE
[1] "11.98"
[1] 2609
[1] TRUE
[1] "11.98"
[1] 2610
[1] TRUE
[1] "1.06"
[1] 2611
[1] TRUE
[1] "1.06"
[1] 2612
[1] TRUE
[1] "1.06"
[1] 2613
[1] TRUE
[1] "1.06"
[1] 2614
[1] TRUE
[1] "5.2"
[1] 2615
[1] TRUE
[1] "5.2"
[1] 2616
[1] TRUE
[1] "5.2"
[1] 2617
[1] TRUE
[1] "5.2"
[1] 2618
[1] TRUE
[1] "0.57999999999999996"
[1] 2619
[1] TRUE
[1] "0.57999999999999996"
[1] 2620
[1] TRUE
[1] "0.57999999999999996"
[1] 2621
[1] TRUE
[1] "0.57999999999999996"
[1] 2622
[1] TRUE
[1] "3.17"
[1] 2623
[1] TRUE
[1] "3.17"
[1] 2624
[1] TRUE
[1] "1.03"
[1] 2625
[1] TRUE
[1] "1.03"
[1] 2626
[1] TRUE
[1] "1.03"
[1] 2627
[1] TRUE
[1] "1.03"
[1] 2628
[1] TRUE
[1] "18.100000000000001"
[1] 2629
[1] TRUE
[1] "18.100000000000001"
[1] 2630
[1] TRUE
[1] "18.100000000000001"
[1] 2631
[1] TRUE
[1] "18.100000000000001"
[1] 2632
[1] TRUE
[1] "9.26"
[1] 2633
[1] TRUE
[1] "9.26"
[1] 2634
[1] TRUE
[1] "24.1"
[1] 2635
[1] TRUE
[1] "24.1"
[1] 2636
[1] TRUE
[1] "24.1"
[1] 2637
[1] TRUE
[1] "24.1"
[1] 2638
[1] TRUE
[1] "24.1"
[1] 2639
[1] TRUE
[1] "24.1"
[1] 2640
[1] TRUE
[1] "2.73"
[1] 2641
[1] TRUE
[1] "2.73"
[1] 2642
[1] TRUE
[1] "0.8"
[1] 2643
[1] TRUE
[1] "0.8"
[1] 2644
[1] TRUE
[1] "0.8"
[1] 2645
[1] TRUE
[1] "0.8"
[1] 2646
[1] TRUE
[1] "1.5"
[1] 2647
[1] TRUE
[1] "1.5"
[1] 2648
[1] TRUE
[1] "1.5"
[1] 2649
[1] TRUE
[1] "1.5"
[1] 2650
[1] TRUE
[1] "1.5"
[1] 2651
[1] TRUE
[1] "1.5"
[1] 2652
[1] TRUE
[1] "2.4700000000000002"
[1] 2653
[1] TRUE
[1] "2.4700000000000002"
[1] 2654
[1] TRUE
[1] "2.4700000000000002"
[1] 2655
[1] TRUE
[1] "2.4700000000000002"
[1] 2656
[1] TRUE
[1] "2.7"
[1] 2657
[1] TRUE
[1] "2.7"
[1] 2658
[1] TRUE
[1] "11.3"
[1] 2659
[1] TRUE
[1] "11.3"
[1] 2660
[1] TRUE
[1] "11.3"
[1] 2661
[1] TRUE
[1] "11.3"
[1] 2662
[1] TRUE
[1] "8.1999999999999993"
[1] 2663
[1] TRUE
[1] "8.1999999999999993"
[1] 2664
[1] TRUE
[1] "8.1999999999999993"
[1] 2665
[1] TRUE
[1] "8.1999999999999993"
[1] 2666
[1] TRUE
[1] "8.1999999999999993"
[1] 2667
[1] TRUE
[1] "8.1999999999999993"
[1] 2668
[1] TRUE
[1] "11.12"
[1] 2669
[1] TRUE
[1] "11.12"
[1] 2670
[1] TRUE
[1] "11.12"
[1] 2671
[1] TRUE
[1] "13.2"
[1] 2672
[1] TRUE
[1] "13.2"
[1] 2673
[1] TRUE
[1] "8.9"
[1] 2674
[1] TRUE
[1] "8.9"
[1] 2675
[1] TRUE
[1] "8.9"
[1] 2676
[1] TRUE
[1] "7.31"
[1] 2677
[1] TRUE
[1] "7.31"
[1] 2678
[1] TRUE
[1] "5.5"
[1] 2679
[1] TRUE
[1] "5.5"
[1] 2680
[1] TRUE
[1] "12"
[1] 2681
[1] TRUE
[1] "12"
[1] 2682
[1] TRUE
[1] "12"
[1] 2683
[1] TRUE
[1] "12"
[1] 2684
[1] TRUE
[1] "11.6"
[1] 2685
[1] TRUE
[1] "11.6"
[1] 2686
[1] TRUE
[1] "11.6"
[1] 2687
[1] TRUE
[1] "11.6"
[1] 2688
[1] TRUE
[1] "10.199999999999999"
[1] 2689
[1] TRUE
[1] "10.199999999999999"
[1] 2690
[1] TRUE
[1] "10.199999999999999"
[1] 2691
[1] TRUE
[1] "10.199999999999999"
[1] 2692
[1] TRUE
[1] "4.7"
[1] 2693
[1] TRUE
[1] "4.7"
[1] 2694
[1] TRUE
[1] "4.7"
[1] 2695
[1] TRUE
[1] "4.7"
[1] 2696
[1] TRUE
[1] "1.5"
[1] 2697
[1] TRUE
[1] "1.5"
[1] 2698
[1] TRUE
[1] "1.5"
[1] 2699
[1] TRUE
[1] "1.5"
[1] 2700
[1] TRUE
[1] "7.01"
[1] 2701
[1] TRUE
[1] "7.01"
[1] 2702
[1] TRUE
[1] "7.01"
[1] 2703
[1] TRUE
[1] "7.01"
[1] 2704
[1] TRUE
[1] "1.76"
[1] 2705
[1] TRUE
[1] "1.76"
[1] 2706
[1] TRUE
[1] "1.76"
[1] 2707
[1] TRUE
[1] "1.76"
[1] 2708
[1] TRUE
[1] "0.7"
[1] 2709
[1] TRUE
[1] "0.7"
[1] 2710
[1] TRUE
[1] "0.7"
[1] 2711
[1] TRUE
[1] "0.7"
[1] 2712
[1] TRUE
[1] "1.6"
[1] 2713
[1] TRUE
[1] "1.6"
[1] 2714
[1] TRUE
[1] "1.6"
[1] 2715
[1] TRUE
[1] "1.6"
[1] 2716
[1] TRUE
[1] "1.2"
[1] 2717
[1] TRUE
[1] "1.2"
[1] 2718
[1] TRUE
[1] "1.2"
[1] 2719
[1] TRUE
[1] "1.2"
[1] 2720
[1] TRUE
[1] "8.6"
[1] 2721
[1] TRUE
[1] "8.6"
[1] 2722
[1] TRUE
[1] "8.6"
[1] 2723
[1] TRUE
[1] "8.6"
[1] 2724
[1] TRUE
[1] "0.9"
[1] 2725
[1] TRUE
[1] "0.9"
[1] 2726
[1] TRUE
[1] "0.9"
[1] 2727
[1] TRUE
[1] "0.9"
[1] 2728
[1] TRUE
[1] "0.8"
[1] 2729
[1] TRUE
[1] "0.8"
[1] 2730
[1] TRUE
[1] "0.8"
[1] 2731
[1] TRUE
[1] "0.8"
[1] 2732
[1] TRUE
[1] "11.3"
[1] 2733
[1] TRUE
[1] "11.3"
[1] 2734
[1] TRUE
[1] "11.3"
[1] 2735
[1] TRUE
[1] "5"
[1] 2736
[1] TRUE
[1] "5"
[1] 2737
[1] TRUE
[1] "5"
[1] 2738
[1] TRUE
[1] "5"
[1] 2739
[1] TRUE
[1] "5"
[1] 2740
[1] TRUE
[1] "5"
[1] 2741
[1] TRUE
[1] "2.42"
[1] 2742
[1] TRUE
[1] "2.42"
[1] 2743
[1] TRUE
[1] "2.42"
[1] 2744
[1] TRUE
[1] "2.42"
[1] 2745
[1] TRUE
[1] "7.8"
[1] 2746
[1] TRUE
[1] "7.8"
[1] 2747
[1] TRUE
[1] "7.8"
[1] 2748
[1] TRUE
[1] "7.8"
[1] 2749
[1] TRUE
[1] "6.59"
[1] 2750
[1] TRUE
[1] "6.59"
[1] 2751
[1] TRUE
[1] "6.59"
[1] 2752
[1] TRUE
[1] "6.59"
[1] 2753
[1] TRUE
[1] "4.0999999999999996"
[1] 2754
[1] TRUE
[1] "4.0999999999999996"
[1] 2755
[1] TRUE
[1] "4.0999999999999996"
[1] 2756
[1] TRUE
[1] "4.0999999999999996"
[1] 2757
[1] TRUE
[1] "5.4"
[1] 2758
[1] TRUE
[1] "5.4"
[1] 2759
[1] TRUE
[1] "5.4"
[1] 2760
[1] TRUE
[1] "0.87"
[1] 2761
[1] TRUE
[1] "0.87"
[1] 2762
[1] TRUE
[1] "0.87"
[1] 2763
[1] TRUE
[1] "0.87"
[1] 2764
[1] TRUE
[1] "1.2"
[1] 2765
[1] TRUE
[1] "1.2"
[1] 2766
[1] TRUE
[1] "1"
[1] 2767
[1] TRUE
[1] "1"
[1] 2768
[1] TRUE
[1] "1"
[1] 2769
[1] TRUE
[1] "1"
[1] 2770
[1] TRUE
[1] "3.2"
[1] 2771
[1] TRUE
[1] "3.2"
[1] 2772
[1] TRUE
[1] "3.2"
[1] 2773
[1] TRUE
[1] "3.2"
[1] 2774
[1] TRUE
[1] "1.3"
[1] 2775
[1] TRUE
[1] "1.3"
[1] 2776
[1] TRUE
[1] "1.3"
[1] 2777
[1] TRUE
[1] "1.3"
[1] 2778
[1] TRUE
[1] "1.2"
[1] 2779
[1] TRUE
[1] "1.2"
[1] 2780
[1] TRUE
[1] "1.2"
[1] 2781
[1] TRUE
[1] "1.2"
[1] 2782
[1] TRUE
[1] "0.9"
[1] 2783
[1] TRUE
[1] "0.9"
[1] 2784
[1] TRUE
[1] "0.9"
[1] 2785
[1] TRUE
[1] "0.9"
[1] 2786
[1] TRUE
[1] "2.75"
[1] 2787
[1] TRUE
[1] "2.75"
[1] 2788
[1] TRUE
[1] "2.75"
[1] 2789
[1] TRUE
[1] "2.75"
[1] 2790
[1] TRUE
[1] "2.75"
[1] 2791
[1] TRUE
[1] "2.75"
[1] 2792
[1] TRUE
[1] "3"
[1] 2793
[1] TRUE
[1] "3"
[1] 2794
[1] TRUE
[1] "3"
[1] 2795
[1] TRUE
[1] "3"
[1] 2796
[1] TRUE
[1] "10.3"
[1] 2797
[1] TRUE
[1] "10.3"
[1] 2798
[1] TRUE
[1] "4.2"
[1] 2799
[1] TRUE
[1] "4.2"
[1] 2800
[1] TRUE
[1] "4.2"
[1] 2801
[1] TRUE
[1] "4.2"
[1] 2802
[1] TRUE
[1] "4.7"
[1] 2803
[1] TRUE
[1] "4.7"
[1] 2804
[1] TRUE
[1] "4.7"
[1] 2805
[1] TRUE
[1] "4.7"
[1] 2806
[1] TRUE
[1] "4.7"
[1] 2807
[1] TRUE
[1] "4.7"
[1] 2808
[1] TRUE
[1] "3.76"
[1] 2809
[1] TRUE
[1] "3.76"
[1] 2810
[1] TRUE
[1] "3.76"
[1] 2811
[1] TRUE
[1] "3.76"
[1] 2812
[1] TRUE
[1] "12.61"
[1] 2813
[1] TRUE
[1] "12.61"
[1] 2814
[1] TRUE
[1] "12.61"
[1] 2815
[1] TRUE
[1] "12.61"
[1] 2816
[1] TRUE
[1] "3.1"
[1] 2817
[1] TRUE
[1] "3.1"
[1] 2818
[1] TRUE
[1] "3.9"
[1] 2819
[1] TRUE
[1] "3.9"
[1] 2820
[1] TRUE
[1] "1.6"
[1] 2821
[1] TRUE
[1] "1.6"
[1] 2822
[1] TRUE
[1] "2.2000000000000002"
[1] 2823
[1] TRUE
[1] "2.2000000000000002"
[1] 2824
[1] TRUE
[1] "1.3"
[1] 2825
[1] TRUE
[1] "1.3"
[1] 2826
[1] TRUE
[1] "1.3"
[1] 2827
[1] TRUE
[1] "1.3"
[1] 2828
[1] TRUE
[1] "8.4"
[1] 2829
[1] TRUE
[1] "8.4"
[1] 2830
[1] TRUE
[1] "1.4"
[1] 2831
[1] TRUE
[1] "1.4"
[1] 2832
[1] TRUE
[1] "1.2"
[1] 2833
[1] TRUE
[1] "1.2"
[1] 2834
[1] TRUE
[1] "1.3"
[1] 2835
[1] TRUE
[1] "1.3"
[1] 2836
[1] TRUE
[1] "4.0999999999999996"
[1] 2837
[1] TRUE
[1] "4.0999999999999996"
[1] 2838
[1] TRUE
[1] "1.2"
[1] 2839
[1] TRUE
[1] "1.2"
[1] 2840
[1] TRUE
[1] "4"
[1] 2841
[1] TRUE
[1] "4"
[1] 2842
[1] TRUE
[1] "1"
[1] 2843
[1] TRUE
[1] "1"
[1] 2844
[1] TRUE
[1] "1.1000000000000001"
[1] 2845
[1] TRUE
[1] "1.1000000000000001"
[1] 2846
[1] TRUE
[1] "1"
[1] 2847
[1] TRUE
[1] "1"
[1] 2848
[1] TRUE
[1] "1.2"
[1] 2849
[1] TRUE
[1] "1.2"
[1] 2850
[1] TRUE
[1] "10.199999999999999"
[1] 2851
[1] TRUE
[1] "10.199999999999999"
[1] 2852
[1] TRUE
[1] "11"
[1] 2853
[1] TRUE
[1] "11"
[1] 2854
[1] TRUE
[1] "0.7"
[1] 2855
[1] TRUE
[1] "0.7"
[1] 2856
[1] TRUE
[1] "0.7"
[1] 2857
[1] TRUE
[1] "0.7"
[1] 2858
[1] TRUE
[1] "8.4"
[1] 2859
[1] TRUE
[1] "8.4"
[1] 2860
[1] TRUE
[1] "8.8000000000000007"
[1] 2861
[1] TRUE
[1] "8.8000000000000007"
[1] 2862
[1] TRUE
[1] "3.4"
[1] 2863
[1] TRUE
[1] "3.4"
[1] 2864
[1] TRUE
[1] "0.7"
[1] 2865
[1] TRUE
[1] "0.7"
[1] 2866
[1] TRUE
[1] "0.7"
[1] 2867
[1] TRUE
[1] "0.7"
[1] 2868
[1] TRUE
[1] "6.3"
[1] 2869
[1] TRUE
[1] "6.3"
[1] 2870
[1] TRUE
[1] "4.2"
[1] 2871
[1] TRUE
[1] "4.2"
[1] 2872
[1] TRUE
[1] "3.9"
[1] 2873
[1] TRUE
[1] "3.9"
[1] 2874
[1] TRUE
[1] "4.0999999999999996"
[1] 2875
[1] TRUE
[1] "4.0999999999999996"
[1] 2876
[1] TRUE
[1] "1.2"
[1] 2877
[1] TRUE
[1] "0.92"
[1] 2878
[1] TRUE
[1] "0.92"
[1] 2879
[1] TRUE
[1] "0.99"
[1] 2880
[1] TRUE
[1] "0.99"
[1] 2881
[1] TRUE
[1] "1.04"
[1] 2882
[1] TRUE
[1] "1.04"
[1] 2883
[1] TRUE
[1] "2.92"
[1] 2884
[1] TRUE
[1] "17.55"
[1] 2885
[1] TRUE
[1] "13.95"
[1] 2886
[1] TRUE
[1] "14.45"
[1] 2887
[1] TRUE
[1] "14.45"
[1] 2888
[1] TRUE
[1] "14.45"
[1] 2889
[1] TRUE
[1] "1.81"
[1] 2890
[1] TRUE
[1] "1.81"
[1] 2891
[1] TRUE
[1] "0.9"
[1] 2892
[1] TRUE
[1] "0.6"
[1] 2893
[1] TRUE
[1] "0.6"
[1] 2894
[1] TRUE
[1] "1.27"
[1] 2895
[1] TRUE
[1] "1.27"
[1] 2896
[1] TRUE
[1] "1.2"
[1] 2897
[1] TRUE
[1] "1.7"
[1] 2898
[1] TRUE
[1] "1.7"
[1] 2899
[1] TRUE
[1] "1.6"
[1] 2900
[1] TRUE
[1] "1.6"
[1] 2901
[1] TRUE
[1] "0.9"
[1] 2902
[1] TRUE
[1] "0.9"
[1] 2903
[1] TRUE
[1] "0.7"
[1] 2904
[1] TRUE
[1] "0.7"
[1] 2905
[1] TRUE
[1] "1.1000000000000001"
[1] 2906
[1] TRUE
[1] "1.1000000000000001"
[1] 2907
[1] TRUE
[1] "8.4"
[1] 2908
[1] TRUE
[1] "2.2000000000000002"
[1] 2909
[1] TRUE
[1] "2.2000000000000002"
[1] 2910
[1] TRUE
[1] "1.3"
[1] 2911
[1] TRUE
[1] "1.3"
[1] 2912
[1] TRUE
[1] "0.5"
[1] 2913
[1] TRUE
[1] "0.9"
[1] 2914
[1] TRUE
[1] "1.31"
[1] 2915
[1] TRUE
[1] "1.31"
[1] 2916
[1] TRUE
[1] "2.4"
[1] 2917
[1] TRUE
[1] "1.73"
[1] 2918
[1] TRUE
[1] "1.73"
[1] 2919
[1] TRUE
[1] "3.8"
[1] 2920
[1] TRUE
[1] "3.8"
[1] 2921
[1] TRUE
[1] "4"
[1] 2922
[1] TRUE
[1] "3.2"
[1] 2923
[1] TRUE
[1] "3.2"
[1] 2924
[1] TRUE
[1] "3.5"
[1] 2925
[1] TRUE
[1] "3.5"
[1] 2926
[1] TRUE
[1] "7.2"
[1] 2927
[1] TRUE
[1] "2.1481250000000003"
[1] 2928
[1] TRUE
[1] "2.1481250000000003"
[1] 2929
[1] TRUE
[1] "2.1481250000000003"
[1] 2930
[1] TRUE
[1] "2.1481250000000003"
[1] 2931
[1] TRUE
[1] "2.4691091954022992"
[1] 2932
[1] TRUE
[1] "2.4691091954022992"
[1] 2933
[1] TRUE
[1] "2.4691091954022992"
[1] 2934
[1] TRUE
[1] "2.4691091954022992"
[1] 2935
[1] TRUE
[1] "2.7191455696202533"
[1] 2936
[1] TRUE
[1] "2.7191455696202533"
[1] 2937
[1] TRUE
[1] "2.686666666666667"
[1] 2938
[1] TRUE
[1] "2.686666666666667"
[1] 2939
[1] TRUE
[1] "2.686666666666667"
[1] 2940
[1] TRUE
[1] "2.686666666666667"
[1] 2941
[1] TRUE
[1] "3.088122605363985"
[1] 2942
[1] TRUE
[1] "3.088122605363985"
[1] 2943
[1] TRUE
[1] "3.088122605363985"
[1] 2944
[1] TRUE
[1] "3.088122605363985"
[1] 2945
[1] TRUE
[1] "1.8999999999999997"
[1] 2946
[1] TRUE
[1] "1.8999999999999997"
[1] 2947
[1] TRUE
[1] "1.8999999999999997"
[1] 2948
[1] TRUE
[1] "1.8999999999999997"
[1] 2949
[1] TRUE
[1] "2.1839080459770113"
[1] 2950
[1] TRUE
[1] "2.1839080459770113"
[1] 2951
[1] TRUE
[1] "2.1839080459770113"
[1] 2952
[1] TRUE
[1] "2.1839080459770113"
[1] 2953
[1] TRUE
[1] "2.40506329113924"
[1] 2954
[1] TRUE
[1] "2.40506329113924"
[1] 2955
[1] TRUE
[1] "3.1433333333333331"
[1] 2956
[1] TRUE
[1] "3.1433333333333331"
[1] 2957
[1] TRUE
[1] "3.1433333333333331"
[1] 2958
[1] TRUE
[1] "3.1433333333333331"
[1] 2959
[1] TRUE
[1] "3.1433333333333331"
[1] 2960
[1] TRUE
[1] "3.1433333333333331"
[1] 2961
[1] TRUE
[1] "3.1433333333333331"
[1] 2962
[1] TRUE
[1] "3.1433333333333331"
[1] 2963
[1] TRUE
[1] "3.6130268199233715"
[1] 2964
[1] TRUE
[1] "3.6130268199233715"
[1] 2965
[1] TRUE
[1] "3.6130268199233715"
[1] 2966
[1] TRUE
[1] "3.6130268199233715"
[1] 2967
[1] TRUE
[1] "3.9789029535864975"
[1] 2968
[1] TRUE
[1] "3.9789029535864975"
[1] 2969
[1] TRUE
[1] "1.1724999999999999"
[1] 2970
[1] TRUE
[1] "1.1724999999999999"
[1] 2971
[1] TRUE
[1] "1.1724999999999999"
[1] 2972
[1] TRUE
[1] "1.1724999999999999"
[1] 2973
[1] TRUE
[1] "1.3477011494252873"
[1] 2974
[1] TRUE
[1] "1.3477011494252873"
[1] 2975
[1] TRUE
[1] "1.3477011494252873"
[1] 2976
[1] TRUE
[1] "1.3477011494252873"
[1] 2977
[1] TRUE
[1] "1.4841772151898731"
[1] 2978
[1] TRUE
[1] "1.4841772151898731"
[1] 2979
[1] TRUE
[1] "4.5506190476190467"
[1] 2980
[1] TRUE
[1] "4.5506190476190467"
[1] 2981
[1] TRUE
[1] "4.5506190476190467"
[1] 2982
[1] TRUE
[1] "4.5506190476190467"
[1] 2983
[1] TRUE
[1] "5.482673551348249"
[1] 2984
[1] TRUE
[1] "5.482673551348249"
[1] 2985
[1] TRUE
[1] "5.482673551348249"
[1] 2986
[1] TRUE
[1] "5.482673551348249"
[1] 2987
[1] TRUE
[1] "6.0674920634920619"
[1] 2988
[1] TRUE
[1] "6.0674920634920619"
[1] 2989
[1] TRUE
[1] "4.2720000000000002"
[1] 2990
[1] TRUE
[1] "4.2720000000000002"
[1] 2991
[1] TRUE
[1] "4.2720000000000002"
[1] 2992
[1] TRUE
[1] "4.2720000000000002"
[1] 2993
[1] TRUE
[1] "5.1469879518072297"
[1] 2994
[1] TRUE
[1] "5.1469879518072297"
[1] 2995
[1] TRUE
[1] "5.1469879518072297"
[1] 2996
[1] TRUE
[1] "5.1469879518072297"
[1] 2997
[1] TRUE
[1] "5.6960000000000006"
[1] 2998
[1] TRUE
[1] "5.6960000000000006"
[1] 2999
[1] TRUE
[1] "3.4632857142857145"
[1] 3000
[1] TRUE
[1] "3.4632857142857145"
[1] 3001
[1] TRUE
[1] "3.4632857142857145"
[1] 3002
[1] TRUE
[1] "3.4632857142857145"
[1] 3003
[1] TRUE
[1] "4.1726333907056805"
[1] 3004
[1] TRUE
[1] "4.1726333907056805"
[1] 3005
[1] TRUE
[1] "4.1726333907056805"
[1] 3006
[1] TRUE
[1] "4.1726333907056805"
[1] 3007
[1] TRUE
[1] "4.6177142857142863"
[1] 3008
[1] TRUE
[1] "4.6177142857142863"
[1] 3009
[1] TRUE
[1] "3.8343333333333329"
[1] 3010
[1] TRUE
[1] "3.8343333333333329"
[1] 3011
[1] TRUE
[1] "3.8343333333333329"
[1] 3012
[1] TRUE
[1] "3.8343333333333329"
[1] 3013
[1] TRUE
[1] "4.6196787148594378"
[1] 3014
[1] TRUE
[1] "4.6196787148594378"
[1] 3015
[1] TRUE
[1] "4.6196787148594378"
[1] 3016
[1] TRUE
[1] "4.6196787148594378"
[1] 3017
[1] TRUE
[1] "5.1124444444444439"
[1] 3018
[1] TRUE
[1] "5.1124444444444439"
[1] 3019
[1] TRUE
[1] "4.0729999999999995"
[1] 3020
[1] TRUE
[1] "4.0729999999999995"
[1] 3021
[1] TRUE
[1] "4.0729999999999995"
[1] 3022
[1] TRUE
[1] "4.0729999999999995"
[1] 3023
[1] TRUE
[1] "4.9072289156626505"
[1] 3024
[1] TRUE
[1] "4.9072289156626505"
[1] 3025
[1] TRUE
[1] "4.9072289156626505"
[1] 3026
[1] TRUE
[1] "4.9072289156626505"
[1] 3027
[1] TRUE
[1] "5.4306666666666663"
[1] 3028
[1] TRUE
[1] "5.4306666666666663"
[1] 3029
[1] TRUE
[1] "4.95"
[1] 3030
[1] TRUE
[1] "4.95"
[1] 3031
[1] TRUE
[1] "4.95"
[1] 3032
[1] TRUE
[1] "4.95"
[1] 3033
[1] TRUE
[1] "5.9638554216867474"
[1] 3034
[1] TRUE
[1] "5.9638554216867474"
[1] 3035
[1] TRUE
[1] "5.9638554216867474"
[1] 3036
[1] TRUE
[1] "5.9638554216867474"
[1] 3037
[1] TRUE
[1] "6.6000000000000005"
[1] 3038
[1] TRUE
[1] "6.6000000000000005"
[1] 3039
[1] TRUE
[1] "0.97749999999999992"
[1] 3040
[1] TRUE
[1] "0.97749999999999992"
[1] 3041
[1] TRUE
[1] "0.97749999999999992"
[1] 3042
[1] TRUE
[1] "0.97749999999999992"
[1] 3043
[1] TRUE
[1] "1.177710843373494"
[1] 3044
[1] TRUE
[1] "1.177710843373494"
[1] 3045
[1] TRUE
[1] "1.177710843373494"
[1] 3046
[1] TRUE
[1] "1.177710843373494"
[1] 3047
[1] TRUE
[1] "1.3033333333333332"
[1] 3048
[1] TRUE
[1] "1.3033333333333332"
[1] 3049
[1] TRUE
[1] "0.82090909090909081"
[1] 3050
[1] TRUE
[1] "0.82090909090909081"
[1] 3051
[1] TRUE
[1] "0.82090909090909081"
[1] 3052
[1] TRUE
[1] "0.82090909090909081"
[1] 3053
[1] TRUE
[1] "0.9890470974808323"
[1] 3054
[1] TRUE
[1] "0.9890470974808323"
[1] 3055
[1] TRUE
[1] "0.9890470974808323"
[1] 3056
[1] TRUE
[1] "0.9890470974808323"
[1] 3057
[1] TRUE
[1] "1.0945454545454545"
[1] 3058
[1] TRUE
[1] "1.0945454545454545"
[1] 3059
[1] TRUE
[1] "0.745"
[1] 3060
[1] TRUE
[1] "0.745"
[1] 3061
[1] TRUE
[1] "0.745"
[1] 3062
[1] TRUE
[1] "0.745"
[1] 3063
[1] TRUE
[1] "0.89759036144578319"
[1] 3064
[1] TRUE
[1] "0.89759036144578319"
[1] 3065
[1] TRUE
[1] "0.89759036144578319"
[1] 3066
[1] TRUE
[1] "0.89759036144578319"
[1] 3067
[1] TRUE
[1] "0.99333333333333329"
[1] 3068
[1] TRUE
[1] "0.99333333333333329"
[1] 3069
[1] TRUE
[1] "5.4019999999999992"
[1] 3070
[1] TRUE
[1] "5.4019999999999992"
[1] 3071
[1] TRUE
[1] "5.4019999999999992"
[1] 3072
[1] TRUE
[1] "5.4019999999999992"
[1] 3073
[1] TRUE
[1] "5.23"
[1] 3074
[1] TRUE
[1] "5.23"
[1] 3075
[1] TRUE
[1] "5.23"
[1] 3076
[1] TRUE
[1] "5.23"
[1] 3077
[1] TRUE
[1] "4.7"
[1] 3078
[1] TRUE
[1] "4.7"
[1] 3079
[1] TRUE
[1] "4.7"
[1] 3080
[1] TRUE
[1] "4.7"
[1] 3081
[1] TRUE
[1] "2.44"
[1] 3082
[1] TRUE
[1] "2.44"
[1] 3083
[1] TRUE
[1] "2.44"
[1] 3084
[1] TRUE
[1] "2.44"
[1] 3085
[1] TRUE
[1] "2.3152631578947371"
[1] 3086
[1] TRUE
[1] "2.3152631578947371"
[1] 3087
[1] TRUE
[1] "2.3152631578947371"
[1] 3088
[1] TRUE
[1] "2.3152631578947371"
[1] 3089
[1] TRUE
[1] "1.9060000000000001"
[1] 3090
[1] TRUE
[1] "1.9060000000000001"
[1] 3091
[1] TRUE
[1] "2.2963855421686752"
[1] 3092
[1] TRUE
[1] "2.2963855421686752"
[1] 3093
[1] TRUE
[1] "2.2963855421686752"
[1] 3094
[1] TRUE
[1] "2.2963855421686752"
[1] 3095
[1] TRUE
[1] "2.5413333333333337"
[1] 3096
[1] TRUE
[1] "2.5413333333333337"
[1] 3097
[1] TRUE
[1] "1.9060000000000001"
[1] 3098
[1] TRUE
[1] "1.9060000000000001"
[1] 3099
[1] TRUE
[1] "2.2963855421686752"
[1] 3100
[1] TRUE
[1] "2.2963855421686752"
[1] 3101
[1] TRUE
[1] "2.2963855421686752"
[1] 3102
[1] TRUE
[1] "2.2963855421686752"
[1] 3103
[1] TRUE
[1] "2.5413333333333337"
[1] 3104
[1] TRUE
[1] "2.5413333333333337"
[1] 3105
[1] TRUE
[1] "17.100000000000001"
[1] 3106
[1] TRUE
[1] "17.100000000000001"
[1] 3107
[1] TRUE
[1] "17.100000000000001"
[1] 3108
[1] TRUE
[1] "17.100000000000001"
[1] 3109
[1] TRUE
[1] "17.734939759036145"
[1] 3110
[1] TRUE
[1] "17.734939759036145"
[1] 3111
[1] TRUE
[1] "20.602409638554221"
[1] 3112
[1] TRUE
[1] "20.602409638554221"
[1] 3113
[1] TRUE
[1] "18.133333333333336"
[1] 3114
[1] TRUE
[1] "18.133333333333336"
[1] 3115
[1] TRUE
[1] "1.9300000000000002"
[1] 3116
[1] TRUE
[1] "1.9300000000000002"
[1] 3117
[1] TRUE
[1] "1.9300000000000002"
[1] 3118
[1] TRUE
[1] "1.9300000000000002"
[1] 3119
[1] TRUE
[1] "2.3253012048192776"
[1] 3120
[1] TRUE
[1] "2.3253012048192776"
[1] 3121
[1] TRUE
[1] "2.3253012048192776"
[1] 3122
[1] TRUE
[1] "2.3253012048192776"
[1] 3123
[1] TRUE
[1] "2.5733333333333337"
[1] 3124
[1] TRUE
[1] "2.5733333333333337"
[1] 3125
[1] TRUE
[1] "12.958124999999999"
[1] 3126
[1] TRUE
[1] "12.958124999999999"
[1] 3127
[1] TRUE
[1] "12.958124999999999"
[1] 3128
[1] TRUE
[1] "12.958124999999999"
[1] 3129
[1] TRUE
[1] "14.178463855421686"
[1] 3130
[1] TRUE
[1] "14.178463855421686"
[1] 3131
[1] TRUE
[1] "15.612198795180722"
[1] 3132
[1] TRUE
[1] "15.612198795180722"
[1] 3133
[1] TRUE
[1] "13.928052325581394"
[1] 3134
[1] TRUE
[1] "13.928052325581394"
[1] 3135
[1] TRUE
[1] "13.47695652173913"
[1] 3136
[1] TRUE
[1] "13.47695652173913"
[1] 3137
[1] TRUE
[1] "13.47695652173913"
[1] 3138
[1] TRUE
[1] "13.47695652173913"
[1] 3139
[1] TRUE
[1] "14.803562074384494"
[1] 3140
[1] TRUE
[1] "14.803562074384494"
[1] 3141
[1] TRUE
[1] "16.237297014143529"
[1] 3142
[1] TRUE
[1] "16.237297014143529"
[1] 3143
[1] TRUE
[1] "14.531344792719917"
[1] 3144
[1] TRUE
[1] "14.531344792719917"
[1] 3145
[1] TRUE
[1] "15.378750000000004"
[1] 3146
[1] TRUE
[1] "15.378750000000004"
[1] 3147
[1] TRUE
[1] "15.378750000000004"
[1] 3148
[1] TRUE
[1] "15.378750000000004"
[1] 3149
[1] TRUE
[1] "15.661144578313257"
[1] 3150
[1] TRUE
[1] "15.661144578313257"
[1] 3151
[1] TRUE
[1] "18.528614457831331"
[1] 3152
[1] TRUE
[1] "18.528614457831331"
[1] 3153
[1] TRUE
[1] "15.603197674418604"
[1] 3154
[1] TRUE
[1] "15.603197674418604"
[1] 3155
[1] TRUE
[1] "12.2"
[1] 3156
[1] TRUE
[1] "12.2"
[1] 3157
[1] TRUE
[1] "12.2"
[1] 3158
[1] TRUE
[1] "12.2"
[1] 3159
[1] TRUE
[1] "13.265060240963855"
[1] 3160
[1] TRUE
[1] "13.265060240963855"
[1] 3161
[1] TRUE
[1] "14.698795180722891"
[1] 3162
[1] TRUE
[1] "14.698795180722891"
[1] 3163
[1] TRUE
[1] "13.046511627906975"
[1] 3164
[1] TRUE
[1] "13.046511627906975"
[1] 3165
[1] TRUE
[1] "15.4"
[1] 3166
[1] TRUE
[1] "15.4"
[1] 3167
[1] TRUE
[1] "15.4"
[1] 3168
[1] TRUE
[1] "15.4"
[1] 3169
[1] TRUE
[1] "15.686746987951807"
[1] 3170
[1] TRUE
[1] "15.686746987951807"
[1] 3171
[1] TRUE
[1] "18.554216867469879"
[1] 3172
[1] TRUE
[1] "18.554216867469879"
[1] 3173
[1] TRUE
[1] "15.627906976744185"
[1] 3174
[1] TRUE
[1] "15.627906976744185"
[1] 3175
[1] TRUE
[1] "6.5"
[1] 3176
[1] TRUE
[1] "6.5"
[1] 3177
[1] TRUE
[1] "6.5"
[1] 3178
[1] TRUE
[1] "6.5"
[1] 3179
[1] TRUE
[1] "6.3975903614457827"
[1] 3180
[1] TRUE
[1] "6.3975903614457827"
[1] 3181
[1] TRUE
[1] "7.8313253012048198"
[1] 3182
[1] TRUE
[1] "7.8313253012048198"
[1] 3183
[1] TRUE
[1] "6.4186046511627906"
[1] 3184
[1] TRUE
[1] "6.4186046511627906"
[1] 3185
[1] TRUE
[1] "10.784285714285714"
[1] 3186
[1] TRUE
[1] "10.784285714285714"
[1] 3187
[1] TRUE
[1] "10.784285714285714"
[1] 3188
[1] TRUE
[1] "10.784285714285714"
[1] 3189
[1] TRUE
[1] "11.559380378657488"
[1] 3190
[1] TRUE
[1] "11.559380378657488"
[1] 3191
[1] TRUE
[1] "12.993115318416523"
[1] 3192
[1] TRUE
[1] "12.993115318416523"
[1] 3193
[1] TRUE
[1] "11.400332225913621"
[1] 3194
[1] TRUE
[1] "11.400332225913621"
[1] 3195
[1] TRUE
[1] "12.43"
[1] 3196
[1] TRUE
[1] "12.43"
[1] 3197
[1] TRUE
[1] "12.43"
[1] 3198
[1] TRUE
[1] "12.43"
[1] 3199
[1] TRUE
[1] "13.542168674698797"
[1] 3200
[1] TRUE
[1] "13.542168674698797"
[1] 3201
[1] TRUE
[1] "14.975903614457831"
[1] 3202
[1] TRUE
[1] "14.975903614457831"
[1] 3203
[1] TRUE
[1] "13.313953488372093"
[1] 3204
[1] TRUE
[1] "13.313953488372093"
[1] 3205
[1] TRUE
[1] "6.67"
[1] 3206
[1] TRUE
[1] "6.67"
[1] 3207
[1] TRUE
[1] "6.67"
[1] 3208
[1] TRUE
[1] "6.67"
[1] 3209
[1] TRUE
[1] "6.6024096385542164"
[1] 3210
[1] TRUE
[1] "6.6024096385542164"
[1] 3211
[1] TRUE
[1] "8.0361445783132535"
[1] 3212
[1] TRUE
[1] "8.0361445783132535"
[1] 3213
[1] TRUE
[1] "6.6162790697674412"
[1] 3214
[1] TRUE
[1] "6.6162790697674412"
[1] 3215
[1] TRUE
[1] "10.981190476190477"
[1] 3216
[1] TRUE
[1] "10.981190476190477"
[1] 3217
[1] TRUE
[1] "10.981190476190477"
[1] 3218
[1] TRUE
[1] "10.80939393939394"
[1] 3219
[1] TRUE
[1] "10.80939393939394"
[1] 3220
[1] TRUE
[1] "10.80939393939394"
[1] 3221
[1] TRUE
[1] "11.866666666666667"
[1] 3222
[1] TRUE
[1] "11.866666666666667"
[1] 3223
[1] TRUE
[1] "11.866666666666667"
[1] 3224
[1] TRUE
[1] "7.2727272727272743"
[1] 3225
[1] TRUE
[1] "7.2727272727272743"
[1] 3226
[1] TRUE
[1] "7.2727272727272743"
[1] 3227
[1] TRUE
[1] "13.014090909090912"
[1] 3228
[1] TRUE
[1] "13.014090909090912"
[1] 3229
[1] TRUE
[1] "13.014090909090912"
[1] 3230
[1] TRUE
[1] "6.4491525423728815"
[1] 3231
[1] TRUE
[1] "6.4491525423728815"
[1] 3232
[1] TRUE
[1] "6.4491525423728815"
[1] 3233
[1] TRUE
[1] "6.4491525423728815"
[1] 3234
[1] TRUE
[1] "6.3879472693032016"
[1] 3235
[1] TRUE
[1] "6.3879472693032016"
[1] 3236
[1] TRUE
[1] "7.1657250470809792"
[1] 3237
[1] TRUE
[1] "7.1657250470809792"
[1] 3238
[1] TRUE
[1] "6.2937853107344628"
[1] 3239
[1] TRUE
[1] "6.2937853107344628"
[1] 3240
[1] TRUE
[1] "6.7884000000000002"
[1] 3241
[1] TRUE
[1] "6.7884000000000002"
[1] 3242
[1] TRUE
[1] "6.7884000000000002"
[1] 3243
[1] TRUE
[1] "6.7884000000000002"
[1] 3244
[1] TRUE
[1] "6.7648888888888887"
[1] 3245
[1] TRUE
[1] "6.7648888888888887"
[1] 3246
[1] TRUE
[1] "7.5426666666666664"
[1] 3247
[1] TRUE
[1] "7.5426666666666664"
[1] 3248
[1] TRUE
[1] "6.7287179487179491"
[1] 3249
[1] TRUE
[1] "6.7287179487179491"
[1] 3250
[1] TRUE
[1] "3.7727272727272734"
[1] 3251
[1] TRUE
[1] "3.7727272727272734"
[1] 3252
[1] TRUE
[1] "3.7727272727272734"
[1] 3253
[1] TRUE
[1] "3.7727272727272734"
[1] 3254
[1] TRUE
[1] "4.1919191919191929"
[1] 3255
[1] TRUE
[1] "4.1919191919191929"
[1] 3256
[1] TRUE
[1] "4.1919191919191929"
[1] 3257
[1] TRUE
[1] "4.1919191919191929"
[1] 3258
[1] TRUE
[1] "4.8368298368298372"
[1] 3259
[1] TRUE
[1] "4.8368298368298372"
[1] 3260
[1] TRUE
[1] "7.2900000000000009"
[1] 3261
[1] TRUE
[1] "7.2900000000000009"
[1] 3262
[1] TRUE
[1] "7.2900000000000009"
[1] 3263
[1] TRUE
[1] "7.2900000000000009"
[1] 3264
[1] TRUE
[1] "7.3222222222222229"
[1] 3265
[1] TRUE
[1] "7.3222222222222229"
[1] 3266
[1] TRUE
[1] "8.1000000000000014"
[1] 3267
[1] TRUE
[1] "8.1000000000000014"
[1] 3268
[1] TRUE
[1] "7.3717948717948723"
[1] 3269
[1] TRUE
[1] "7.3717948717948723"
[1] 3270
[1] TRUE
[1] "13.25"
[1] 3271
[1] TRUE
[1] "13.25"
[1] 3272
[1] TRUE
[1] "13.25"
[1] 3273
[1] TRUE
[1] "13.25"
[1] 3274
[1] TRUE
[1] "13.944444444444445"
[1] 3275
[1] TRUE
[1] "13.944444444444445"
[1] 3276
[1] TRUE
[1] "14.722222222222221"
[1] 3277
[1] TRUE
[1] "14.722222222222221"
[1] 3278
[1] TRUE
[1] "15.012820512820513"
[1] 3279
[1] TRUE
[1] "15.012820512820513"
[1] 3280
[1] TRUE
[1] "5.79"
[1] 3281
[1] TRUE
[1] "5.79"
[1] 3282
[1] TRUE
[1] "5.79"
[1] 3283
[1] TRUE
[1] "5.79"
[1] 3284
[1] TRUE
[1] "5.655555555555555"
[1] 3285
[1] TRUE
[1] "5.655555555555555"
[1] 3286
[1] TRUE
[1] "6.4333333333333336"
[1] 3287
[1] TRUE
[1] "6.4333333333333336"
[1] 3288
[1] TRUE
[1] "5.4487179487179489"
[1] 3289
[1] TRUE
[1] "5.4487179487179489"
[1] 3290
[1] TRUE
[1] "5.2159999999999993"
[1] 3291
[1] TRUE
[1] "5.2159999999999993"
[1] 3292
[1] TRUE
[1] "5.2159999999999993"
[1] 3293
[1] TRUE
[1] "5.2159999999999993"
[1] 3294
[1] TRUE
[1] "5.017777777777777"
[1] 3295
[1] TRUE
[1] "5.017777777777777"
[1] 3296
[1] TRUE
[1] "5.7955555555555547"
[1] 3297
[1] TRUE
[1] "5.7955555555555547"
[1] 3298
[1] TRUE
[1] "4.7128205128205121"
[1] 3299
[1] TRUE
[1] "4.7128205128205121"
[1] 3300
[1] TRUE
[1] "1.108888888888889"
[1] 3301
[1] TRUE
[1] "1.108888888888889"
[1] 3302
[1] TRUE
[1] "1.108888888888889"
[1] 3303
[1] TRUE
[1] "1.108888888888889"
[1] 3304
[1] TRUE
[1] "1.3360107095046856"
[1] 3305
[1] TRUE
[1] "1.3360107095046856"
[1] 3306
[1] TRUE
[1] "1.3360107095046856"
[1] 3307
[1] TRUE
[1] "1.3360107095046856"
[1] 3308
[1] TRUE
[1] "1.5401234567901236"
[1] 3309
[1] TRUE
[1] "1.5401234567901236"
[1] 3310
[1] TRUE
[1] "0.82250000000000001"
[1] 3311
[1] TRUE
[1] "0.82250000000000001"
[1] 3312
[1] TRUE
[1] "0.82250000000000001"
[1] 3313
[1] TRUE
[1] "0.82250000000000001"
[1] 3314
[1] TRUE
[1] "0.99096385542168686"
[1] 3315
[1] TRUE
[1] "0.99096385542168686"
[1] 3316
[1] TRUE
[1] "0.99096385542168686"
[1] 3317
[1] TRUE
[1] "0.99096385542168686"
[1] 3318
[1] TRUE
[1] "1.1423611111111112"
[1] 3319
[1] TRUE
[1] "1.1423611111111112"
[1] 3320
[1] TRUE
[1] "0.61898305084745742"
[1] 3321
[1] TRUE
[1] "0.61898305084745742"
[1] 3322
[1] TRUE
[1] "0.61898305084745742"
[1] 3323
[1] TRUE
[1] "0.61898305084745742"
[1] 3324
[1] TRUE
[1] "0.75485737908226513"
[1] 3325
[1] TRUE
[1] "0.75485737908226513"
[1] 3326
[1] TRUE
[1] "0.75485737908226513"
[1] 3327
[1] TRUE
[1] "0.75485737908226513"
[1] 3328
[1] TRUE
[1] "0.82531073446327652"
[1] 3329
[1] TRUE
[1] "0.82531073446327652"
[1] 3330
[1] TRUE
[1] "0.70666666666666667"
[1] 3331
[1] TRUE
[1] "0.70666666666666667"
[1] 3332
[1] TRUE
[1] "0.70666666666666667"
[1] 3333
[1] TRUE
[1] "0.70666666666666667"
[1] 3334
[1] TRUE
[1] "0.86178861788617889"
[1] 3335
[1] TRUE
[1] "0.86178861788617889"
[1] 3336
[1] TRUE
[1] "0.86178861788617889"
[1] 3337
[1] TRUE
[1] "0.86178861788617889"
[1] 3338
[1] TRUE
[1] "0.94222222222222218"
[1] 3339
[1] TRUE
[1] "0.94222222222222218"
[1] 3340
[1] TRUE
[1] "0.61857142857142822"
[1] 3341
[1] TRUE
[1] "0.61857142857142822"
[1] 3342
[1] TRUE
[1] "0.61857142857142822"
[1] 3343
[1] TRUE
[1] "0.61857142857142822"
[1] 3344
[1] TRUE
[1] "0.75435540069686369"
[1] 3345
[1] TRUE
[1] "0.75435540069686369"
[1] 3346
[1] TRUE
[1] "0.75435540069686369"
[1] 3347
[1] TRUE
[1] "0.75435540069686369"
[1] 3348
[1] TRUE
[1] "0.82476190476190425"
[1] 3349
[1] TRUE
[1] "0.82476190476190425"
[1] 3350
[1] TRUE
[1] "0.61120370370370347"
[1] 3351
[1] TRUE
[1] "0.61120370370370347"
[1] 3352
[1] TRUE
[1] "0.61120370370370347"
[1] 3353
[1] TRUE
[1] "0.61120370370370347"
[1] 3354
[1] TRUE
[1] "0.74537037037037013"
[1] 3355
[1] TRUE
[1] "0.74537037037037013"
[1] 3356
[1] TRUE
[1] "0.74537037037037013"
[1] 3357
[1] TRUE
[1] "0.74537037037037013"
[1] 3358
[1] TRUE
[1] "0.81493827160493792"
[1] 3359
[1] TRUE
[1] "0.81493827160493792"
[1] 3360
[1] TRUE
[1] "0.58295081967213103"
[1] 3361
[1] TRUE
[1] "0.58295081967213103"
[1] 3362
[1] TRUE
[1] "0.58295081967213103"
[1] 3363
[1] TRUE
[1] "0.58295081967213103"
[1] 3364
[1] TRUE
[1] "0.71091563374650124"
[1] 3365
[1] TRUE
[1] "0.71091563374650124"
[1] 3366
[1] TRUE
[1] "0.71091563374650124"
[1] 3367
[1] TRUE
[1] "0.71091563374650124"
[1] 3368
[1] TRUE
[1] "0.77726775956284133"
[1] 3369
[1] TRUE
[1] "0.77726775956284133"
[1] 3370
[1] TRUE
[1] "0.61120370370370347"
[1] 3371
[1] TRUE
[1] "0.61120370370370347"
[1] 3372
[1] TRUE
[1] "0.61120370370370347"
[1] 3373
[1] TRUE
[1] "0.61120370370370347"
[1] 3374
[1] TRUE
[1] "0.74537037037037013"
[1] 3375
[1] TRUE
[1] "0.74537037037037013"
[1] 3376
[1] TRUE
[1] "0.74537037037037013"
[1] 3377
[1] TRUE
[1] "0.74537037037037013"
[1] 3378
[1] TRUE
[1] "0.81493827160493792"
[1] 3379
[1] TRUE
[1] "0.81493827160493792"
[1] 3380
[1] TRUE
[1] "0.91"
[1] 3381
[1] TRUE
[1] "0.91"
[1] 3382
[1] TRUE
[1] "0.91"
[1] 3383
[1] TRUE
[1] "0.91"
[1] 3384
[1] TRUE
[1] "1.1097560975609757"
[1] 3385
[1] TRUE
[1] "1.1097560975609757"
[1] 3386
[1] TRUE
[1] "1.1097560975609757"
[1] 3387
[1] TRUE
[1] "1.1097560975609757"
[1] 3388
[1] TRUE
[1] "1.2133333333333334"
[1] 3389
[1] TRUE
[1] "1.2133333333333334"
[1] 3390
[1] TRUE
[1] "0.8666666666666667"
[1] 3391
[1] TRUE
[1] "0.8666666666666667"
[1] 3392
[1] TRUE
[1] "0.8666666666666667"
[1] 3393
[1] TRUE
[1] "0.8666666666666667"
[1] 3394
[1] TRUE
[1] "1.0569105691056913"
[1] 3395
[1] TRUE
[1] "1.0569105691056913"
[1] 3396
[1] TRUE
[1] "1.0569105691056913"
[1] 3397
[1] TRUE
[1] "1.0569105691056913"
[1] 3398
[1] TRUE
[1] "1.1555555555555557"
[1] 3399
[1] TRUE
[1] "1.1555555555555557"
[1] 3400
[1] TRUE
[1] "0.48666666666666675"
[1] 3401
[1] TRUE
[1] "0.48666666666666675"
[1] 3402
[1] TRUE
[1] "0.48666666666666675"
[1] 3403
[1] TRUE
[1] "0.48666666666666675"
[1] 3404
[1] TRUE
[1] "0.59349593495934971"
[1] 3405
[1] TRUE
[1] "0.59349593495934971"
[1] 3406
[1] TRUE
[1] "0.59349593495934971"
[1] 3407
[1] TRUE
[1] "0.59349593495934971"
[1] 3408
[1] TRUE
[1] "0.64888888888888896"
[1] 3409
[1] TRUE
[1] "0.64888888888888896"
[1] 3410
[1] TRUE
[1] "0.57333333333333336"
[1] 3411
[1] TRUE
[1] "0.57333333333333336"
[1] 3412
[1] TRUE
[1] "0.57333333333333336"
[1] 3413
[1] TRUE
[1] "0.57333333333333336"
[1] 3414
[1] TRUE
[1] "0.69918699186991873"
[1] 3415
[1] TRUE
[1] "0.69918699186991873"
[1] 3416
[1] TRUE
[1] "0.69918699186991873"
[1] 3417
[1] TRUE
[1] "0.69918699186991873"
[1] 3418
[1] TRUE
[1] "0.76444444444444448"
[1] 3419
[1] TRUE
[1] "0.76444444444444448"
[1] 3420
[1] TRUE
[1] "0.2"
[1] 3421
[1] TRUE
[1] "0.2"
[1] 3422
[1] TRUE
[1] "0.24390243902439027"
[1] 3423
[1] TRUE
[1] "0.24390243902439027"
[1] 3424
[1] TRUE
[1] "0.24390243902439027"
[1] 3425
[1] TRUE
[1] "0.24390243902439027"
[1] 3426
[1] TRUE
[1] "0.26666666666666666"
[1] 3427
[1] TRUE
[1] "0.26666666666666666"
[1] 3428
[1] TRUE
[1] "0.41"
[1] 3429
[1] TRUE
[1] "0.41"
[1] 3430
[1] TRUE
[1] "0.41"
[1] 3431
[1] TRUE
[1] "0.41"
[1] 3432
[1] TRUE
[1] "0.5"
[1] 3433
[1] TRUE
[1] "0.5"
[1] 3434
[1] TRUE
[1] "0.5"
[1] 3435
[1] TRUE
[1] "0.5"
[1] 3436
[1] TRUE
[1] "0.54666666666666663"
[1] 3437
[1] TRUE
[1] "0.54666666666666663"
[1] 3438
[1] TRUE
[1] "4.2433333333333341"
[1] 3439
[1] TRUE
[1] "4.2433333333333341"
[1] 3440
[1] TRUE
[1] "4.2433333333333341"
[1] 3441
[1] TRUE
[1] "4.2433333333333341"
[1] 3442
[1] TRUE
[1] "4.9341085271317837"
[1] 3443
[1] TRUE
[1] "4.9341085271317837"
[1] 3444
[1] TRUE
[1] "4.9341085271317837"
[1] 3445
[1] TRUE
[1] "4.9341085271317837"
[1] 3446
[1] TRUE
[1] "5.6577777777777785"
[1] 3447
[1] TRUE
[1] "5.6577777777777785"
[1] 3448
[1] TRUE
[1] "2.9"
[1] 3449
[1] TRUE
[1] "2.9"
[1] 3450
[1] TRUE
[1] "2.9"
[1] 3451
[1] TRUE
[1] "2.9"
[1] 3452
[1] TRUE
[1] "3.3720930232558137"
[1] 3453
[1] TRUE
[1] "3.3720930232558137"
[1] 3454
[1] TRUE
[1] "3.3720930232558137"
[1] 3455
[1] TRUE
[1] "3.3720930232558137"
[1] 3456
[1] TRUE
[1] "3.8666666666666667"
[1] 3457
[1] TRUE
[1] "3.8666666666666667"
[1] 3458
[1] TRUE
[1] "6.2233333333333327"
[1] 3459
[1] TRUE
[1] "6.2233333333333327"
[1] 3460
[1] TRUE
[1] "6.2233333333333327"
[1] 3461
[1] TRUE
[1] "6.2233333333333327"
[1] 3462
[1] TRUE
[1] "6.0968992248062008"
[1] 3463
[1] TRUE
[1] "6.0968992248062008"
[1] 3464
[1] TRUE
[1] "7.2364341085271313"
[1] 3465
[1] TRUE
[1] "7.2364341085271313"
[1] 3466
[1] TRUE
[1] "5.9644444444444433"
[1] 3467
[1] TRUE
[1] "5.9644444444444433"
[1] 3468
[1] TRUE
[1] "5.4"
[1] 3469
[1] TRUE
[1] "5.4"
[1] 3470
[1] TRUE
[1] "5.4"
[1] 3471
[1] TRUE
[1] "5.4"
[1] 3472
[1] TRUE
[1] "5.4"
[1] 3473
[1] TRUE
[1] "5.4"
[1] 3474
[1] TRUE
[1] "4.7142857142857153"
[1] 3475
[1] TRUE
[1] "4.7142857142857153"
[1] 3476
[1] TRUE
[1] "4.7142857142857153"
[1] 3477
[1] TRUE
[1] "7.7142857142857153"
[1] 3478
[1] TRUE
[1] "7.7142857142857153"
[1] 3479
[1] TRUE
[1] "7.7142857142857153"
[1] 3480
[1] TRUE
[1] "5"
[1] 3481
[1] TRUE
[1] "5"
[1] 3482
[1] TRUE
[1] "5"
[1] 3483
[1] TRUE
[1] "9.1781249999999996"
[1] 3484
[1] TRUE
[1] "9.1781249999999996"
[1] 3485
[1] TRUE
[1] "9.1781249999999996"
[1] 3486
[1] TRUE
[1] "9.1781249999999996"
[1] 3487
[1] TRUE
[1] "9.1781249999999996"
[1] 3488
[1] TRUE
[1] "9.1781249999999996"
[1] 3489
[1] TRUE
[1] "10.111607142857144"
[1] 3490
[1] TRUE
[1] "10.111607142857144"
[1] 3491
[1] TRUE
[1] "10.111607142857144"
[1] 3492
[1] TRUE
[1] "13.111607142857142"
[1] 3493
[1] TRUE
[1] "13.111607142857142"
[1] 3494
[1] TRUE
[1] "13.111607142857142"
[1] 3495
[1] TRUE
[1] "9.7226562499999982"
[1] 3496
[1] TRUE
[1] "9.7226562499999982"
[1] 3497
[1] TRUE
[1] "9.7226562499999982"
[1] 3498
[1] TRUE
[1] "2.6241176470588234"
[1] 3499
[1] TRUE
[1] "2.6241176470588234"
[1] 3500
[1] TRUE
[1] "2.6241176470588234"
[1] 3501
[1] TRUE
[1] "2.6241176470588234"
[1] 3502
[1] TRUE
[1] "2.6241176470588234"
[1] 3503
[1] TRUE
[1] "2.6241176470588234"
[1] 3504
[1] TRUE
[1] "3.7487394957983193"
[1] 3505
[1] TRUE
[1] "3.7487394957983193"
[1] 3506
[1] TRUE
[1] "3.7487394957983193"
[1] 3507
[1] TRUE
[1] "3.7487394957983193"
[1] 3508
[1] TRUE
[1] "3.7487394957983193"
[1] 3509
[1] TRUE
[1] "3.7487394957983193"
[1] 3510
[1] TRUE
[1] "3.2801470588235291"
[1] 3511
[1] TRUE
[1] "3.2801470588235291"
[1] 3512
[1] TRUE
[1] "3.2801470588235291"
[1] 3513
[1] TRUE
[1] "1.1308333333333336"
[1] 3514
[1] TRUE
[1] "1.1308333333333336"
[1] 3515
[1] TRUE
[1] "1.2159498207885306"
[1] 3516
[1] TRUE
[1] "1.2159498207885306"
[1] 3517
[1] TRUE
[1] "0.76166666666666671"
[1] 3518
[1] TRUE
[1] "0.76166666666666671"
[1] 3519
[1] TRUE
[1] "0.81899641577060933"
[1] 3520
[1] TRUE
[1] "0.81899641577060933"
[1] 3521
[1] TRUE
[1] "0.95000000000000007"
[1] 3522
[1] TRUE
[1] "0.95000000000000007"
[1] 3523
[1] TRUE
[1] "1.021505376344086"
[1] 3524
[1] TRUE
[1] "1.021505376344086"
[1] 3525
[1] TRUE
[1] "1.4805882352941175"
[1] 3526
[1] TRUE
[1] "1.4805882352941175"
[1] 3527
[1] TRUE
[1] "1.7838412473423104"
[1] 3528
[1] TRUE
[1] "1.7838412473423104"
[1] 3529
[1] TRUE
[1] "1.5123076923076924"
[1] 3530
[1] TRUE
[1] "1.5123076923076924"
[1] 3531
[1] TRUE
[1] "1.8220574606116777"
[1] 3532
[1] TRUE
[1] "1.8220574606116777"
[1] 3533
[1] TRUE
[1] "1.36"
[1] 3534
[1] TRUE
[1] "1.36"
[1] 3535
[1] TRUE
[1] "1.63855421686747"
[1] 3536
[1] TRUE
[1] "1.63855421686747"
[1] 3537
[1] TRUE
[1] "1.8939999999999997"
[1] 3538
[1] TRUE
[1] "1.8939999999999997"
[1] 3539
[1] TRUE
[1] "2.2819277108433731"
[1] 3540
[1] TRUE
[1] "2.2819277108433731"
[1] 3541
[1] TRUE
[1] "0.99199999999999999"
[1] 3542
[1] TRUE
[1] "0.99199999999999999"
[1] 3543
[1] TRUE
[1] "1.1402298850574712"
[1] 3544
[1] TRUE
[1] "1.1402298850574712"
[1] 3545
[1] TRUE
[1] "1.0149999999999999"
[1] 3546
[1] TRUE
[1] "1.0149999999999999"
[1] 3547
[1] TRUE
[1] "1.1666666666666665"
[1] 3548
[1] TRUE
[1] "1.1666666666666665"
[1] 3549
[1] TRUE
[1] "0.9"
[1] 3550
[1] TRUE
[1] "0.9"
[1] 3551
[1] TRUE
[1] "1.0344827586206897"
[1] 3552
[1] TRUE
[1] "1.0344827586206897"
[1] 3553
[1] TRUE
[1] "1.06"
[1] 3554
[1] TRUE
[1] "1.06"
[1] 3555
[1] TRUE
[1] "1.2183908045977012"
[1] 3556
[1] TRUE
[1] "1.2183908045977012"
[1] 3557
[1] TRUE
[1] "1.1031818181818183"
[1] 3558
[1] TRUE
[1] "1.1031818181818183"
[1] 3559
[1] TRUE
[1] "1.2680250783699061"
[1] 3560
[1] TRUE
[1] "1.2680250783699061"
[1] 3561
[1] TRUE
[1] "0.87750000000000006"
[1] 3562
[1] TRUE
[1] "0.87750000000000006"
[1] 3563
[1] TRUE
[1] "1.0086206896551724"
[1] 3564
[1] TRUE
[1] "1.0086206896551724"
[1] 3565
[1] TRUE
[1] "0.88833333333333331"
[1] 3566
[1] TRUE
[1] "0.88833333333333331"
[1] 3567
[1] TRUE
[1] "1.0210727969348659"
[1] 3568
[1] TRUE
[1] "1.0210727969348659"
[1] 3569
[1] TRUE
[1] "1.665"
[1] 3570
[1] TRUE
[1] "1.665"
[1] 3571
[1] TRUE
[1] "1.913793103448276"
[1] 3572
[1] TRUE
[1] "1.913793103448276"
[1] 3573
[1] TRUE
[1] "0.71181818181818191"
[1] 3574
[1] TRUE
[1] "0.71181818181818191"
[1] 3575
[1] TRUE
[1] "0.79979570990806959"
[1] 3576
[1] TRUE
[1] "0.79979570990806959"
[1] 3577
[1] TRUE
[1] "0.64999999999999991"
[1] 3578
[1] TRUE
[1] "0.64999999999999991"
[1] 3579
[1] TRUE
[1] "0.73033707865168529"
[1] 3580
[1] TRUE
[1] "0.73033707865168529"
[1] 3581
[1] TRUE
[1] "0.4"
[1] 3582
[1] TRUE
[1] "0.4"
[1] 3583
[1] TRUE
[1] "0.44943820224719105"
[1] 3584
[1] TRUE
[1] "0.44943820224719105"
[1] 3585
[1] TRUE
[1] "0.56874999999999998"
[1] 3586
[1] TRUE
[1] "0.56874999999999998"
[1] 3587
[1] TRUE
[1] "0.6390449438202247"
[1] 3588
[1] TRUE
[1] "0.6390449438202247"
[1] 3589
[1] TRUE
[1] "1.1399999999999999"
[1] 3590
[1] TRUE
[1] "1.1399999999999999"
[1] 3591
[1] TRUE
[1] "1.2808988764044942"
[1] 3592
[1] TRUE
[1] "1.2808988764044942"
[1] 3593
[1] TRUE
[1] "0.89500000000000002"
[1] 3594
[1] TRUE
[1] "0.89500000000000002"
[1] 3595
[1] TRUE
[1] "1.0056179775280898"
[1] 3596
[1] TRUE
[1] "1.0056179775280898"
[1] 3597
[1] TRUE
[1] "0.70857142857142841"
[1] 3598
[1] TRUE
[1] "0.70857142857142841"
[1] 3599
[1] TRUE
[1] "0.81444991789819354"
[1] 3600
[1] TRUE
[1] "0.81444991789819354"
[1] 3601
[1] TRUE
[1] "0.72666666666666657"
[1] 3602
[1] TRUE
[1] "0.72666666666666657"
[1] 3603
[1] TRUE
[1] "0.83524904214559381"
[1] 3604
[1] TRUE
[1] "0.83524904214559381"
[1] 3605
[1] TRUE
[1] "1.1216666666666664"
[1] 3606
[1] TRUE
[1] "1.1216666666666664"
[1] 3607
[1] TRUE
[1] "0.77499999999999991"
[1] 3608
[1] TRUE
[1] "0.77499999999999991"
[1] 3609
[1] TRUE
[1] "1.0903225806451613"
[1] 3610
[1] TRUE
[1] "1.0903225806451613"
[1] 3611
[1] TRUE
[1] "1.3136416634279053"
[1] 3612
[1] TRUE
[1] "1.3136416634279053"
[1] 3613
[1] TRUE
[1] "0.75"
[1] 3614
[1] TRUE
[1] "0.75"
[1] 3615
[1] TRUE
[1] "0.90361445783132532"
[1] 3616
[1] TRUE
[1] "0.90361445783132532"
[1] 3617
[1] TRUE
[1] "1.1200000000000001"
[1] 3618
[1] TRUE
[1] "1.1200000000000001"
[1] 3619
[1] TRUE
[1] "1.3493975903614459"
[1] 3620
[1] TRUE
[1] "1.3493975903614459"
[1] 3621
[1] TRUE
[1] "1.4620000000000002"
[1] 3622
[1] TRUE
[1] "1.4620000000000002"
[1] 3623
[1] TRUE
[1] "1.7614457831325305"
[1] 3624
[1] TRUE
[1] "1.7614457831325305"
[1] 3625
[1] TRUE
[1] "0.92"
[1] 3626
[1] TRUE
[1] "0.92"
[1] 3627
[1] TRUE
[1] "1.1084337349397591"
[1] 3628
[1] TRUE
[1] "1.1084337349397591"
[1] 3629
[1] TRUE
[1] "0.85"
[1] 3630
[1] TRUE
[1] "0.85"
[1] 3631
[1] TRUE
[1] "1.0240963855421688"
[1] 3632
[1] TRUE
[1] "1.0240963855421688"
[1] 3633
[1] TRUE
[1] "0.6"
[1] 3634
[1] TRUE
[1] "0.6"
[1] 3635
[1] TRUE
[1] "0.72289156626506024"
[1] 3636
[1] TRUE
[1] "0.72289156626506024"
[1] 3637
[1] TRUE
[1] "1.0916666666666663"
[1] 3638
[1] TRUE
[1] "1.0916666666666663"
[1] 3639
[1] TRUE
[1] "1.3152610441767065"
[1] 3640
[1] TRUE
[1] "1.3152610441767065"
[1] 3641
[1] TRUE
[1] "1.1255555555555554"
[1] 3642
[1] TRUE
[1] "1.1255555555555554"
[1] 3643
[1] TRUE
[1] "1.356091030789826"
[1] 3644
[1] TRUE
[1] "1.356091030789826"
[1] 3645
[1] TRUE
[1] "1.0903225806451613"
[1] 3646
[1] TRUE
[1] "1.0903225806451613"
[1] 3647
[1] TRUE
[1] "1.3136416634279053"
[1] 3648
[1] TRUE
[1] "1.3136416634279053"
[1] 3649
[1] TRUE
[1] "1"
[1] 3650
[1] TRUE
[1] "1"
[1] 3651
[1] TRUE
[1] "1.2048192771084338"
[1] 3652
[1] TRUE
[1] "1.2048192771084338"
[1] 3653
[1] TRUE
[1] "1.5150000000000001"
[1] 3654
[1] TRUE
[1] "1.5150000000000001"
[1] 3655
[1] TRUE
[1] "1.8253012048192774"
[1] 3656
[1] TRUE
[1] "1.8253012048192774"
[1] 3657
[1] TRUE
[1] "1.0933333333333333"
[1] 3658
[1] TRUE
[1] "1.0933333333333333"
[1] 3659
[1] TRUE
[1] "1.7791678571428571"
[1] 3660
[1] TRUE
[1] "1.7791678571428571"
[1] 3661
[1] TRUE
[1] "1.8162136363636363"
[1] 3662
[1] TRUE
[1] "1.8162136363636363"
[1] 3663
[1] TRUE
[1] "1.6309277777777778"
[1] 3664
[1] TRUE
[1] "1.6309277777777778"
[1] 3665
[1] TRUE
[1] "1.65"
[1] 3666
[1] TRUE
[1] "1.65"
[1] 3667
[1] TRUE
[1] "1.3719999999999999"
[1] 3668
[1] TRUE
[1] "1.3719999999999999"
[1] 3669
[1] TRUE
[1] "1.375"
[1] 3670
[1] TRUE
[1] "1.375"
[1] 3671
[1] TRUE
[1] "1.2"
[1] 3672
[1] TRUE
[1] "1.2"
[1] 3673
[1] TRUE
[1] "2.08"
[1] 3674
[1] TRUE
[1] "2.08"
[1] 3675
[1] TRUE
[1] "1.6"
[1] 3676
[1] TRUE
[1] "1.6"
[1] 3677
[1] TRUE
[1] "2.0083341875"
[1] 3678
[1] TRUE
[1] "2.0083341875"
[1] 3679
[1] TRUE
[1] "2.5658367499999999"
[1] 3680
[1] TRUE
[1] "2.5658367499999999"
[1] 3681
[1] TRUE
[1] "1.9133333333333333"
[1] 3682
[1] TRUE
[1] "1.9133333333333333"
[1] 3683
[1] TRUE
[1] "1.8199999999999998"
[1] 3684
[1] TRUE
[1] "1.8199999999999998"
[1] 3685
[1] TRUE
[1] "1.7879999999999998"
[1] 3686
[1] TRUE
[1] "1.7879999999999998"
[1] 3687
[1] TRUE
[1] "1.9"
[1] 3688
[1] TRUE
[1] "1.9"
[1] 3689
[1] TRUE
[1] "1.9825000000000002"
[1] 3690
[1] TRUE
[1] "1.9825000000000002"
[1] 3691
[1] TRUE
[1] "1.81"
[1] 3692
[1] TRUE
[1] "1.81"
[1] 3693
[1] TRUE
[1] "0.9"
[1] 3694
[1] TRUE
[1] "0.9"
[1] 3695
[1] TRUE
[1] "0.73571428571428577"
[1] 3696
[1] TRUE
[1] "0.73571428571428577"
[1] 3697
[1] TRUE
[1] "0.8"
[1] 3698
[1] TRUE
[1] "0.8"
[1] 3699
[1] TRUE
[1] "1.1864516129032259"
[1] 3700
[1] TRUE
[1] "1.1864516129032259"
[1] 3701
[1] TRUE
[1] "1.5653846153846152"
[1] 3702
[1] TRUE
[1] "1.5653846153846152"
[1] 3703
[1] TRUE
[1] "1.5628571428571427"
[1] 3704
[1] TRUE
[1] "1.5628571428571427"
[1] 3705
[1] TRUE
[1] "3.064425770308123"
[1] 3706
[1] TRUE
[1] "3.064425770308123"
[1] 3707
[1] TRUE
[1] "2.5620608899297421"
[1] 3708
[1] TRUE
[1] "1.7962499999999999"
[1] 3709
[1] TRUE
[1] "1.7962499999999999"
[1] 3710
[1] TRUE
[1] "3.5220588235294117"
[1] 3711
[1] TRUE
[1] "3.5220588235294117"
[1] 3712
[1] TRUE
[1] "2.944672131147541"
[1] 3713
[1] TRUE
[1] "1.968"
[1] 3714
[1] TRUE
[1] "1.968"
[1] 3715
[1] TRUE
[1] "3.8588235294117648"
[1] 3716
[1] TRUE
[1] "3.8588235294117648"
[1] 3717
[1] TRUE
[1] "3.2262295081967212"
[1] 3718
[1] TRUE
[1] "0.72000000000000008"
[1] 3719
[1] TRUE
[1] "0.72000000000000008"
[1] 3720
[1] TRUE
[1] "1.411764705882353"
[1] 3721
[1] TRUE
[1] "1.411764705882353"
[1] 3722
[1] TRUE
[1] "1.1803278688524592"
[1] 3723
[1] TRUE
[1] "0.82124999999999992"
[1] 3724
[1] TRUE
[1] "0.82124999999999992"
[1] 3725
[1] TRUE
[1] "1.6102941176470587"
[1] 3726
[1] TRUE
[1] "1.6102941176470587"
[1] 3727
[1] TRUE
[1] "1.346311475409836"
[1] 3728
[1] TRUE
[1] "0.77399999999999991"
[1] 3729
[1] TRUE
[1] "0.77399999999999991"
[1] 3730
[1] TRUE
[1] "1.5176470588235291"
[1] 3731
[1] TRUE
[1] "1.5176470588235291"
[1] 3732
[1] TRUE
[1] "1.2688524590163934"
[1] 3733
[1] TRUE
[1] "1.63"
[1] 3734
[1] TRUE
[1] "1.63"
[1] 3735
[1] TRUE
[1] "3.1960784313725488"
[1] 3736
[1] TRUE
[1] "3.1960784313725488"
[1] 3737
[1] TRUE
[1] "2.6721311475409837"
[1] 3738
[1] TRUE
[1] "1.0399999999999998"
[1] 3739
[1] TRUE
[1] "1.0399999999999998"
[1] 3740
[1] TRUE
[1] "2.0392156862745092"
[1] 3741
[1] TRUE
[1] "2.0392156862745092"
[1] 3742
[1] TRUE
[1] "1.7049180327868849"
[1] 3743
[1] TRUE
[1] "1.1018181818181818"
[1] 3744
[1] TRUE
[1] "1.1018181818181818"
[1] 3745
[1] TRUE
[1] "2.1604278074866308"
[1] 3746
[1] TRUE
[1] "2.1604278074866308"
[1] 3747
[1] TRUE
[1] "1.8062593144560357"
[1] 3748
[1] TRUE
[1] "100"
[1] 3749
[1] TRUE
[1] "100"
[1] 3750
[1] TRUE
[1] "100"
[1] 3751
[1] TRUE
[1] "100"
[1] 3752
[1] TRUE
[1] "100"
[1] 3753
[1] TRUE
[1] "100"
[1] 3754
[1] TRUE
[1] "100"
[1] 3755
[1] TRUE
[1] "100"
[1] 3756
[1] TRUE
[1] "100"
[1] 3757
[1] TRUE
[1] "100"
[1] 3758
[1] TRUE
[1] "100"
[1] 3759
[1] TRUE
[1] "100"
[1] 3760
[1] TRUE
[1] "100"
[1] 3761
[1] TRUE
[1] "100"
[1] 3762
[1] TRUE
[1] "100"
[1] 3763
[1] TRUE
[1] "100"
[1] 3764
[1] TRUE
[1] "100"
[1] 3765
[1] TRUE
[1] "100"
[1] 3766
[1] TRUE
[1] "100"
[1] 3767
[1] TRUE
[1] "100"
[1] 3768
[1] TRUE
[1] "100"
[1] 3769
[1] TRUE
[1] "100"
[1] 3770
[1] TRUE
[1] "100"
[1] 3771
[1] TRUE
[1] "100"
[1] 3772
[1] TRUE
[1] "100"
[1] 3773
[1] TRUE
[1] "100"
[1] 3774
[1] TRUE
[1] "100"
[1] 3775
[1] TRUE
[1] "0.03"
[1] 3776
[1] TRUE
[1] "0.16"
[1] 3777
[1] TRUE
[1] "0.56"
[1] 3778
[1] TRUE
[1] "0.28"
[1] 3779
[1] TRUE
[1] "0.3"
[1] 3780
[1] TRUE
[1] "0.3"
[1] 3781
[1] TRUE
[1] "0.39"
[1] 3782
[1] TRUE
[1] "7.72"
[1] 3783
[1] TRUE
[1] "0.64"
[1] 3784
[1] TRUE
[1] "4.84"
[1] 3785
[1] TRUE
[1] "4.84"
[1] 3786
[1] TRUE
[1] "4.84"
[1] 3787
[1] TRUE
[1] "4.84"
[1] 3788
[1] TRUE
[1] "4.84"
[1] 3789
[1] TRUE
[1] "4.84"
[1] 3790
[1] TRUE
[1] "4.84"
[1] 3791
[1] TRUE
[1] "4.84"
[1] 3792
[1] TRUE
[1] "4.84"
[1] 3793
[1] TRUE
[1] "4.84"
[1] 3794
[1] TRUE
[1] "4.84"
[1] 3795
[1] TRUE
[1] "4.84"
[1] 3796
[1] TRUE
[1] "9.71"
[1] 3797
[1] TRUE
[1] "9.71"
[1] 3798
[1] TRUE
[1] "9.71"
[1] 3799
[1] TRUE
[1] "2.33"
[1] 3800
[1] TRUE
[1] "2.33"
[1] 3801
[1] TRUE
[1] "2.33"
[1] 3802
[1] TRUE
[1] "2.33"
[1] 3803
[1] TRUE
[1] "4.24"
[1] 3804
[1] TRUE
[1] "4.24"
[1] 3805
[1] TRUE
[1] "4.24"
[1] 3806
[1] TRUE
[1] "4.24"
[1] 3807
[1] TRUE
[1] "4.24"
[1] 3808
[1] TRUE
[1] "4.24"
[1] 3809
[1] TRUE
[1] "4.24"
[1] 3810
[1] TRUE
[1] "4.24"
[1] 3811
[1] TRUE
[1] "4.24"
[1] 3812
[1] TRUE
[1] "4.24"
[1] 3813
[1] TRUE
[1] "4.24"
[1] 3814
[1] TRUE
[1] "4.24"
[1] 3815
[1] TRUE
[1] "0.81"
[1] 3816
[1] TRUE
[1] "0.81"
[1] 3817
[1] TRUE
[1] "0.81"
[1] 3818
[1] TRUE
[1] "0.81"
[1] 3819
[1] TRUE
[1] "8.02"
[1] 3820
[1] TRUE
[1] "8.02"
[1] 3821
[1] TRUE
[1] "8.02"
[1] 3822
[1] TRUE
[1] "8.02"
[1] 3823
[1] TRUE
[1] "8.02"
[1] 3824
[1] TRUE
[1] "8.02"
[1] 3825
[1] TRUE
[1] "8.02"
[1] 3826
[1] TRUE
[1] "8.02"
[1] 3827
[1] TRUE
[1] "8.02"
[1] 3828
[1] TRUE
[1] "8.02"
[1] 3829
[1] TRUE
[1] "8.02"
[1] 3830
[1] TRUE
[1] "8.02"
[1] 3831
[1] TRUE
[1] "5.6"
[1] 3832
[1] TRUE
[1] "5.6"
[1] 3833
[1] TRUE
[1] "5.6"
[1] 3834
[1] TRUE
[1] "5.6"
[1] 3835
[1] TRUE
[1] "7.17"
[1] 3836
[1] TRUE
[1] "7.17"
[1] 3837
[1] TRUE
[1] "2.82"
[1] 3838
[1] TRUE
[1] "2.82"
[1] 3839
[1] TRUE
[1] "2.82"
[1] 3840
[1] TRUE
[1] "2.82"
[1] 3841
[1] TRUE
[1] "13.33"
[1] 3842
[1] TRUE
[1] "13.33"
[1] 3843
[1] TRUE
[1] "17.9"
[1] 3844
[1] TRUE
[1] "17.9"
[1] 3845
[1] TRUE
[1] "1.91"
[1] 3846
[1] TRUE
[1] "1.91"
[1] 3847
[1] TRUE
[1] "1.91"
[1] 3848
[1] TRUE
[1] "1.91"
[1] 3849
[1] TRUE
[1] "11.9"
[1] 3850
[1] TRUE
[1] "11.9"
[1] 3851
[1] TRUE
[1] "11.9"
[1] 3852
[1] TRUE
[1] "0.67"
[1] 3853
[1] TRUE
[1] "0.67"
[1] 3854
[1] TRUE
[1] "0.67"
[1] 3855
[1] TRUE
[1] "0.67"
[1] 3856
[1] TRUE
[1] "0.86"
[1] 3857
[1] TRUE
[1] "0.86"
[1] 3858
[1] TRUE
[1] "0.86"
[1] 3859
[1] TRUE
[1] "0.86"
[1] 3860
[1] TRUE
[1] "0.41"
[1] 3861
[1] TRUE
[1] "0.41"
[1] 3862
[1] TRUE
[1] "3.17"
[1] 3863
[1] TRUE
[1] "3.17"
[1] 3864
[1] TRUE
[1] "3.17"
[1] 3865
[1] TRUE
[1] "3.17"
[1] 3866
[1] TRUE
[1] "12.67"
[1] 3867
[1] TRUE
[1] "12.67"
[1] 3868
[1] TRUE
[1] "0.7"
[1] 3869
[1] TRUE
[1] "0.7"
[1] 3870
[1] TRUE
[1] "0.7"
[1] 3871
[1] TRUE
[1] "0.7"
[1] 3872
[1] TRUE
[1] "0.7"
[1] 3873
[1] TRUE
[1] "0.7"
[1] 3874
[1] TRUE
[1] "0.7"
[1] 3875
[1] TRUE
[1] "0.7"
[1] 3876
[1] TRUE
[1] "0.7"
[1] 3877
[1] TRUE
[1] "0.7"
[1] 3878
[1] TRUE
[1] "0.7"
[1] 3879
[1] TRUE
[1] "0.7"
[1] 3880
[1] TRUE
[1] "4.93"
[1] 3881
[1] TRUE
[1] "4.93"
[1] 3882
[1] TRUE
[1] "4.93"
[1] 3883
[1] TRUE
[1] "4.93"
[1] 3884
[1] TRUE
[1] "11.66"
[1] 3885
[1] TRUE
[1] "11.66"
[1] 3886
[1] TRUE
[1] "11.66"
[1] 3887
[1] TRUE
[1] "11.66"
[1] 3888
[1] TRUE
[1] "11.66"
[1] 3889
[1] TRUE
[1] "11.66"
[1] 3890
[1] TRUE
[1] "11.66"
[1] 3891
[1] TRUE
[1] "11.66"
[1] 3892
[1] TRUE
[1] "14.95"
[1] 3893
[1] TRUE
[1] "14.95"
[1] 3894
[1] TRUE
[1] "16.23"
[1] 3895
[1] TRUE
[1] "16.23"
[1] 3896
[1] TRUE
[1] "1.93"
[1] 3897
[1] TRUE
[1] "1.93"
[1] 3898
[1] TRUE
[1] "1.93"
[1] 3899
[1] TRUE
[1] "1.93"
[1] 3900
[1] TRUE
[1] "2.37"
[1] 3901
[1] TRUE
[1] "2.37"
[1] 3902
[1] TRUE
[1] "1.73"
[1] 3903
[1] TRUE
[1] "1.73"
[1] 3904
[1] TRUE
[1] "1.02"
[1] 3905
[1] TRUE
[1] "1.02"
[1] 3906
[1] TRUE
[1] "1.02"
[1] 3907
[1] TRUE
[1] "1.02"
[1] 3908
[1] TRUE
[1] "1.3"
[1] 3909
[1] TRUE
[1] "1.3"
[1] 3910
[1] TRUE
[1] "0.45"
[1] 3911
[1] TRUE
[1] "0.45"
[1] 3912
[1] TRUE
[1] "0.45"
[1] 3913
[1] TRUE
[1] "0.45"
[1] 3914
[1] TRUE
[1] "0.55"
[1] 3915
[1] TRUE
[1] "0.55"
[1] 3916
[1] TRUE
[1] "0.96"
[1] 3917
[1] TRUE
[1] "0.96"
[1] 3918
[1] TRUE
[1] "1.33"
[1] 3919
[1] TRUE
[1] "1.33"
[1] 3920
[1] TRUE
[1] "1.33"
[1] 3921
[1] TRUE
[1] "1.33"
[1] 3922
[1] TRUE
[1] "1.61"
[1] 3923
[1] TRUE
[1] "1.61"
[1] 3924
[1] TRUE
[1] "13.84"
[1] 3925
[1] TRUE
[1] "13.84"
[1] 3926
[1] TRUE
[1] "13.84"
[1] 3927
[1] TRUE
[1] "13.84"
[1] 3928
[1] TRUE
[1] "9.04"
[1] 3929
[1] TRUE
[1] "9.04"
[1] 3930
[1] TRUE
[1] "9.04"
[1] 3931
[1] TRUE
[1] "9.04"
[1] 3932
[1] TRUE
[1] "9.04"
[1] 3933
[1] TRUE
[1] "9.04"
[1] 3934
[1] TRUE
[1] "9.04"
[1] 3935
[1] TRUE
[1] "9.04"
[1] 3936
[1] TRUE
[1] "9.04"
[1] 3937
[1] TRUE
[1] "9.04"
[1] 3938
[1] TRUE
[1] "9.04"
[1] 3939
[1] TRUE
[1] "9.04"
[1] 3940
[1] TRUE
[1] "11.59"
[1] 3941
[1] TRUE
[1] "11.59"
[1] 3942
[1] TRUE
[1] "11.59"
[1] 3943
[1] TRUE
[1] "12.37"
[1] 3944
[1] TRUE
[1] "12.37"
[1] 3945
[1] TRUE
[1] "12.37"
[1] 3946
[1] TRUE
[1] "13.88"
[1] 3947
[1] TRUE
[1] "13.88"
[1] 3948
[1] TRUE
[1] "13.88"
[1] 3949
[1] TRUE
[1] "13.88"
[1] 3950
[1] TRUE
[1] "13.88"
[1] 3951
[1] TRUE
[1] "13.88"
[1] 3952
[1] TRUE
[1] "13.88"
[1] 3953
[1] TRUE
[1] "13.88"
[1] 3954
[1] TRUE
[1] "13.88"
[1] 3955
[1] TRUE
[1] "13.88"
[1] 3956
[1] TRUE
[1] "13.88"
[1] 3957
[1] TRUE
[1] "13.88"
[1] 3958
[1] TRUE
[1] "0.64"
[1] 3959
[1] TRUE
[1] "0.64"
[1] 3960
[1] TRUE
[1] "0.64"
[1] 3961
[1] TRUE
[1] "0.64"
[1] 3962
[1] TRUE
[1] "1.06"
[1] 3963
[1] TRUE
[1] "1.06"
[1] 3964
[1] TRUE
[1] "1.06"
[1] 3965
[1] TRUE
[1] "1.06"
[1] 3966
[1] TRUE
[1] "13.89"
[1] 3967
[1] TRUE
[1] "13.89"
[1] 3968
[1] TRUE
[1] "13.89"
[1] 3969
[1] TRUE
[1] "13.89"
[1] 3970
[1] TRUE
[1] "13.89"
[1] 3971
[1] TRUE
[1] "13.89"
[1] 3972
[1] TRUE
[1] "13.89"
[1] 3973
[1] TRUE
[1] "13.89"
[1] 3974
[1] TRUE
[1] "13.89"
[1] 3975
[1] TRUE
[1] "13.89"
[1] 3976
[1] TRUE
[1] "13.89"
[1] 3977
[1] TRUE
[1] "13.89"
[1] 3978
[1] TRUE
[1] "17.81"
[1] 3979
[1] TRUE
[1] "17.81"
[1] 3980
[1] TRUE
[1] "17.81"
[1] 3981
[1] TRUE
[1] "6.3"
[1] 3982
[1] TRUE
[1] "6.3"
[1] 3983
[1] TRUE
[1] "6.3"
[1] 3984
[1] TRUE
[1] "2"
[1] 3985
[1] TRUE
[1] "2"
[1] 3986
[1] TRUE
[1] "2"
[1] 3987
[1] TRUE
[1] "2"
[1] 3988
[1] TRUE
[1] "2"
[1] 3989
[1] TRUE
[1] "2"
[1] 3990
[1] TRUE
[1] "2"
[1] 3991
[1] TRUE
[1] "2"
[1] 3992
[1] TRUE
[1] "2"
[1] 3993
[1] TRUE
[1] "2"
[1] 3994
[1] TRUE
[1] "2"
[1] 3995
[1] TRUE
[1] "2"
[1] 3996
[1] TRUE
[1] "7.89"
[1] 3997
[1] TRUE
[1] "7.89"
[1] 3998
[1] TRUE
[1] "7.89"
[1] 3999
[1] TRUE
[1] "7.89"
[1] 4000
[1] TRUE
[1] "7.89"
[1] 4001
[1] TRUE
[1] "7.89"
[1] 4002
[1] TRUE
[1] "7.89"
[1] 4003
[1] TRUE
[1] "7.89"
[1] 4004
[1] TRUE
[1] "7.89"
[1] 4005
[1] TRUE
[1] "7.89"
[1] 4006
[1] TRUE
[1] "7.89"
[1] 4007
[1] TRUE
[1] "7.89"
[1] 4008
[1] TRUE
[1] "6.3"
[1] 4009
[1] TRUE
[1] "6.3"
[1] 4010
[1] TRUE
[1] "6.3"
[1] 4011
[1] TRUE
[1] "6.3"
[1] 4012
[1] TRUE
[1] "6.3"
[1] 4013
[1] TRUE
[1] "6.3"
[1] 4014
[1] TRUE
[1] "6.3"
[1] 4015
[1] TRUE
[1] "6.3"
[1] 4016
[1] TRUE
[1] "6.3"
[1] 4017
[1] TRUE
[1] "6.3"
[1] 4018
[1] TRUE
[1] "6.3"
[1] 4019
[1] TRUE
[1] "6.3"
[1] 4020
[1] TRUE
[1] "6.32"
[1] 4021
[1] TRUE
[1] "6.32"
[1] 4022
[1] TRUE
[1] "6.32"
[1] 4023
[1] TRUE
[1] "6.73"
[1] 4024
[1] TRUE
[1] "6.73"
[1] 4025
[1] TRUE
[1] "6.73"
[1] 4026
[1] TRUE
[1] "6.73"
[1] 4027
[1] TRUE
[1] "3.79"
[1] 4028
[1] TRUE
[1] "3.79"
[1] 4029
[1] TRUE
[1] "3.79"
[1] 4030
[1] TRUE
[1] "3.79"
[1] 4031
[1] TRUE
[1] "4.86"
[1] 4032
[1] TRUE
[1] "4.86"
[1] 4033
[1] TRUE
[1] "1.54"
[1] 4034
[1] TRUE
[1] "1.54"
[1] 4035
[1] TRUE
[1] "1.54"
[1] 4036
[1] TRUE
[1] "1.54"
[1] 4037
[1] TRUE
[1] "1.87"
[1] 4038
[1] TRUE
[1] "1.87"
[1] 4039
[1] TRUE
[1] "0.91"
[1] 4040
[1] TRUE
[1] "0.91"
[1] 4041
[1] TRUE
[1] "0.91"
[1] 4042
[1] TRUE
[1] "0.91"
[1] 4043
[1] TRUE
[1] "0.92"
[1] 4044
[1] TRUE
[1] "0.92"
[1] 4045
[1] TRUE
[1] "0.92"
[1] 4046
[1] TRUE
[1] "0.92"
[1] 4047
[1] TRUE
[1] "1.18"
[1] 4048
[1] TRUE
[1] "1.18"
[1] 4049
[1] TRUE
[1] "0.69"
[1] 4050
[1] TRUE
[1] "0.69"
[1] 4051
[1] TRUE
[1] "0.69"
[1] 4052
[1] TRUE
[1] "0.69"
[1] 4053
[1] TRUE
[1] "0.88"
[1] 4054
[1] TRUE
[1] "0.88"
[1] 4055
[1] TRUE
[1] "1.22"
[1] 4056
[1] TRUE
[1] "1.22"
[1] 4057
[1] TRUE
[1] "1.22"
[1] 4058
[1] TRUE
[1] "1.22"
[1] 4059
[1] TRUE
[1] "0.98"
[1] 4060
[1] TRUE
[1] "0.98"
[1] 4061
[1] TRUE
[1] "0.98"
[1] 4062
[1] TRUE
[1] "0.98"
[1] 4063
[1] TRUE
[1] "1.18"
[1] 4064
[1] TRUE
[1] "1.18"
[1] 4065
[1] TRUE
[1] "9.47"
[1] 4066
[1] TRUE
[1] "9.47"
[1] 4067
[1] TRUE
[1] "9.47"
[1] 4068
[1] TRUE
[1] "9.47"
[1] 4069
[1] TRUE
[1] "9.47"
[1] 4070
[1] TRUE
[1] "9.47"
[1] 4071
[1] TRUE
[1] "9.47"
[1] 4072
[1] TRUE
[1] "9.47"
[1] 4073
[1] TRUE
[1] "9.47"
[1] 4074
[1] TRUE
[1] "9.47"
[1] 4075
[1] TRUE
[1] "9.47"
[1] 4076
[1] TRUE
[1] "9.47"
[1] 4077
[1] TRUE
[1] "12.14"
[1] 4078
[1] TRUE
[1] "12.14"
[1] 4079
[1] TRUE
[1] "12.14"
[1] 4080
[1] TRUE
[1] "1.34"
[1] 4081
[1] TRUE
[1] "1.34"
[1] 4082
[1] TRUE
[1] "1.34"
[1] 4083
[1] TRUE
[1] "1.34"
[1] 4084
[1] TRUE
[1] "1.62"
[1] 4085
[1] TRUE
[1] "1.62"
[1] 4086
[1] TRUE
[1] "0.7"
[1] 4087
[1] TRUE
[1] "0.7"
[1] 4088
[1] TRUE
[1] "0.7"
[1] 4089
[1] TRUE
[1] "0.7"
[1] 4090
[1] TRUE
[1] "15.3"
[1] 4091
[1] TRUE
[1] "15.3"
[1] 4092
[1] TRUE
[1] "15.3"
[1] 4093
[1] TRUE
[1] "15.3"
[1] 4094
[1] TRUE
[1] "20.14"
[1] 4095
[1] TRUE
[1] "20.14"
[1] 4096
[1] TRUE
[1] "6.34"
[1] 4097
[1] TRUE
[1] "6.34"
[1] 4098
[1] TRUE
[1] "6.34"
[1] 4099
[1] TRUE
[1] "6.34"
[1] 4100
[1] TRUE
[1] "4.32"
[1] 4101
[1] TRUE
[1] "4.32"
[1] 4102
[1] TRUE
[1] "4.32"
[1] 4103
[1] TRUE
[1] "10.43"
[1] 4104
[1] TRUE
[1] "10.43"
[1] 4105
[1] TRUE
[1] "10.43"
[1] 4106
[1] TRUE
[1] "10.43"
[1] 4107
[1] TRUE
[1] "3.77"
[1] 4108
[1] TRUE
[1] "3.77"
[1] 4109
[1] TRUE
[1] "3.77"
[1] 4110
[1] TRUE
[1] "3.77"
[1] 4111
[1] TRUE
[1] "5.5"
[1] 4112
[1] TRUE
[1] "5.5"
[1] 4113
[1] TRUE
[1] "5.93"
[1] 4114
[1] TRUE
[1] "5.93"
[1] 4115
[1] TRUE
[1] "5.93"
[1] 4116
[1] TRUE
[1] "5.93"
[1] 4117
[1] TRUE
[1] "7.5"
[1] 4118
[1] TRUE
[1] "7.5"
[1] 4119
[1] TRUE
[1] "4.4"
[1] 4120
[1] TRUE
[1] "4.4"
[1] 4121
[1] TRUE
[1] "4.4"
[1] 4122
[1] TRUE
[1] "4.4"
[1] 4123
[1] TRUE
[1] "4.97"
[1] 4124
[1] TRUE
[1] "4.97"
[1] 4125
[1] TRUE
[1] "4.69"
[1] 4126
[1] TRUE
[1] "4.69"
[1] 4127
[1] TRUE
[1] "4.69"
[1] 4128
[1] TRUE
[1] "4.69"
[1] 4129
[1] TRUE
[1] "5.57"
[1] 4130
[1] TRUE
[1] "5.57"
[1] 4131
[1] TRUE
[1] "7.39"
[1] 4132
[1] TRUE
[1] "7.39"
[1] 4133
[1] TRUE
[1] "11.45"
[1] 4134
[1] TRUE
[1] "11.45"
[1] 4135
[1] TRUE
[1] "11.45"
[1] 4136
[1] TRUE
[1] "10.45"
[1] 4137
[1] TRUE
[1] "10.45"
[1] 4138
[1] TRUE
[1] "10.45"
[1] 4139
[1] TRUE
[1] "2.73"
[1] 4140
[1] TRUE
[1] "2.73"
[1] 4141
[1] TRUE
[1] "2.73"
[1] 4142
[1] TRUE
[1] "2.73"
[1] 4143
[1] TRUE
[1] "2"
[1] 4144
[1] TRUE
[1] "2"
[1] 4145
[1] TRUE
[1] "2"
[1] 4146
[1] TRUE
[1] "2"
[1] 4147
[1] TRUE
[1] "2.56"
[1] 4148
[1] TRUE
[1] "2.56"
[1] 4149
[1] TRUE
[1] "3.61"
[1] 4150
[1] TRUE
[1] "3.61"
[1] 4151
[1] TRUE
[1] "3.61"
[1] 4152
[1] TRUE
[1] "3.61"
[1] 4153
[1] TRUE
[1] "13.77"
[1] 4154
[1] TRUE
[1] "13.77"
[1] 4155
[1] TRUE
[1] "13.77"
[1] 4156
[1] TRUE
[1] "13.77"
[1] 4157
[1] TRUE
[1] "13.77"
[1] 4158
[1] TRUE
[1] "13.77"
[1] 4159
[1] TRUE
[1] "13.77"
[1] 4160
[1] TRUE
[1] "13.77"
[1] 4161
[1] TRUE
[1] "13.82"
[1] 4162
[1] TRUE
[1] "13.82"
[1] 4163
[1] TRUE
[1] "2.41"
[1] 4164
[1] TRUE
[1] "2.41"
[1] 4165
[1] TRUE
[1] "2.41"
[1] 4166
[1] TRUE
[1] "2.41"
[1] 4167
[1] TRUE
[1] "1.63"
[1] 4168
[1] TRUE
[1] "1.63"
[1] 4169
[1] TRUE
[1] "2.42"
[1] 4170
[1] TRUE
[1] "2.42"
[1] 4171
[1] TRUE
[1] "2.42"
[1] 4172
[1] TRUE
[1] "2.42"
[1] 4173
[1] TRUE
[1] "3.1"
[1] 4174
[1] TRUE
[1] "3.1"
[1] 4175
[1] TRUE
[1] "1.34"
[1] 4176
[1] TRUE
[1] "1.34"
[1] 4177
[1] TRUE
[1] "1.34"
[1] 4178
[1] TRUE
[1] "1.34"
[1] 4179
[1] TRUE
[1] "1.72"
[1] 4180
[1] TRUE
[1] "1.72"
[1] 4181
[1] TRUE
[1] "4.04"
[1] 4182
[1] TRUE
[1] "4.04"
[1] 4183
[1] TRUE
[1] "4.04"
[1] 4184
[1] TRUE
[1] "4.04"
[1] 4185
[1] TRUE
[1] "5.18"
[1] 4186
[1] TRUE
[1] "5.18"
[1] 4187
[1] TRUE
[1] "4.4"
[1] 4188
[1] TRUE
[1] "4.4"
[1] 4189
[1] TRUE
[1] "4.4"
[1] 4190
[1] TRUE
[1] "0.9"
[1] 4191
[1] TRUE
[1] "0.9"
[1] 4192
[1] TRUE
[1] "6.65"
[1] 4193
[1] TRUE
[1] "6.65"
[1] 4194
[1] TRUE
[1] "6.65"
[1] 4195
[1] TRUE
[1] "6.65"
[1] 4196
[1] TRUE
[1] "6.65"
[1] 4197
[1] TRUE
[1] "6.65"
[1] 4198
[1] TRUE
[1] "6.65"
[1] 4199
[1] TRUE
[1] "6.65"
[1] 4200
[1] TRUE
[1] "6.65"
[1] 4201
[1] TRUE
[1] "6.65"
[1] 4202
[1] TRUE
[1] "6.65"
[1] 4203
[1] TRUE
[1] "6.65"
[1] 4204
[1] TRUE
[1] "7.93"
[1] 4205
[1] TRUE
[1] "7.93"
[1] 4206
[1] TRUE
[1] "7.93"
[1] 4207
[1] TRUE
[1] "2.31"
[1] 4208
[1] TRUE
[1] "2.31"
[1] 4209
[1] TRUE
[1] "2.31"
[1] 4210
[1] TRUE
[1] "2.31"
[1] 4211
[1] TRUE
[1] "4.69"
[1] 4212
[1] TRUE
[1] "4.69"
[1] 4213
[1] TRUE
[1] "6.61"
[1] 4214
[1] TRUE
[1] "6.61"
[1] 4215
[1] TRUE
[1] "6.61"
[1] 4216
[1] TRUE
[1] "6.61"
[1] 4217
[1] TRUE
[1] "3.46"
[1] 4218
[1] TRUE
[1] "3.46"
[1] 4219
[1] TRUE
[1] "3.46"
[1] 4220
[1] TRUE
[1] "3.46"
[1] 4221
[1] TRUE
[1] "5.82"
[1] 4222
[1] TRUE
[1] "5.82"
[1] 4223
[1] TRUE
[1] "4.9"
[1] 4224
[1] TRUE
[1] "4.9"
[1] 4225
[1] TRUE
[1] "4.9"
[1] 4226
[1] TRUE
[1] "4.9"
[1] 4227
[1] TRUE
[1] "4.9"
[1] 4228
[1] TRUE
[1] "4.9"
[1] 4229
[1] TRUE
[1] "4.9"
[1] 4230
[1] TRUE
[1] "4.9"
[1] 4231
[1] TRUE
[1] "4.9"
[1] 4232
[1] TRUE
[1] "4.9"
[1] 4233
[1] TRUE
[1] "4.9"
[1] 4234
[1] TRUE
[1] "4.9"
[1] 4235
[1] TRUE
[1] "6.28"
[1] 4236
[1] TRUE
[1] "6.28"
[1] 4237
[1] TRUE
[1] "6.28"
[1] 4238
[1] TRUE
[1] "8.21"
[1] 4239
[1] TRUE
[1] "8.21"
[1] 4240
[1] TRUE
[1] "8.21"
[1] 4241
[1] TRUE
[1] "0.96"
[1] 4242
[1] TRUE
[1] "0.96"
[1] 4243
[1] TRUE
[1] "0.96"
[1] 4244
[1] TRUE
[1] "1.01"
[1] 4245
[1] TRUE
[1] "1.01"
[1] 4246
[1] TRUE
[1] "1.01"
[1] 4247
[1] TRUE
[1] "1.01"
[1] 4248
[1] TRUE
[1] "1.01"
[1] 4249
[1] TRUE
[1] "1.01"
[1] 4250
[1] TRUE
[1] "1.01"
[1] 4251
[1] TRUE
[1] "1.01"
[1] 4252
[1] TRUE
[1] "1.01"
[1] 4253
[1] TRUE
[1] "1.01"
[1] 4254
[1] TRUE
[1] "1.01"
[1] 4255
[1] TRUE
[1] "1.01"
[1] 4256
[1] TRUE
[1] "8.08"
[1] 4257
[1] TRUE
[1] "8.08"
[1] 4258
[1] TRUE
[1] "8.08"
[1] 4259
[1] TRUE
[1] "2.97"
[1] 4260
[1] TRUE
[1] "2.97"
[1] 4261
[1] TRUE
[1] "2.97"
[1] 4262
[1] TRUE
[1] "0.49"
[1] 4263
[1] TRUE
[1] "0.49"
[1] 4264
[1] TRUE
[1] "0.49"
[1] 4265
[1] TRUE
[1] "0.49"
[1] 4266
[1] TRUE
[1] "0.49"
[1] 4267
[1] TRUE
[1] "0.49"
[1] 4268
[1] TRUE
[1] "0.49"
[1] 4269
[1] TRUE
[1] "0.49"
[1] 4270
[1] TRUE
[1] "0.49"
[1] 4271
[1] TRUE
[1] "0.49"
[1] 4272
[1] TRUE
[1] "0.49"
[1] 4273
[1] TRUE
[1] "0.49"
[1] 4274
[1] TRUE
[1] "9.26"
[1] 4275
[1] TRUE
[1] "9.26"
[1] 4276
[1] TRUE
[1] "9.26"
[1] 4277
[1] TRUE
[1] "2.95"
[1] 4278
[1] TRUE
[1] "2.95"
[1] 4279
[1] TRUE
[1] "2.95"
[1] 4280
[1] TRUE
[1] "2.95"
[1] 4281
[1] TRUE
[1] "5.86"
[1] 4282
[1] TRUE
[1] "5.86"
[1] 4283
[1] TRUE
[1] "5.86"
[1] 4284
[1] TRUE
[1] "5.86"
[1] 4285
[1] TRUE
[1] "0.93"
[1] 4286
[1] TRUE
[1] "0.93"
[1] 4287
[1] TRUE
[1] "0.93"
[1] 4288
[1] TRUE
[1] "0.93"
[1] 4289
[1] TRUE
[1] "0.93"
[1] 4290
[1] TRUE
[1] "1.31"
[1] 4291
[1] TRUE
[1] "1.31"
[1] 4292
[1] TRUE
[1] "1.31"
[1] 4293
[1] TRUE
[1] "1.31"
[1] 4294
[1] TRUE
[1] "1.69"
[1] 4295
[1] TRUE
[1] "1.69"
[1] 4296
[1] TRUE
[1] "2.39"
[1] 4297
[1] TRUE
[1] "2.39"
[1] 4298
[1] TRUE
[1] "2.39"
[1] 4299
[1] TRUE
[1] "2.39"
[1] 4300
[1] TRUE
[1] "5.24"
[1] 4301
[1] TRUE
[1] "5.24"
[1] 4302
[1] TRUE
[1] "5.24"
[1] 4303
[1] TRUE
[1] "5.24"
[1] 4304
[1] TRUE
[1] "5.24"
[1] 4305
[1] TRUE
[1] "5.24"
[1] 4306
[1] TRUE
[1] "5.24"
[1] 4307
[1] TRUE
[1] "5.24"
[1] 4308
[1] TRUE
[1] "5.24"
[1] 4309
[1] TRUE
[1] "5.24"
[1] 4310
[1] TRUE
[1] "5.24"
[1] 4311
[1] TRUE
[1] "5.24"
[1] 4312
[1] TRUE
[1] "0.6"
[1] 4313
[1] TRUE
[1] "0.6"
[1] 4314
[1] TRUE
[1] "1.54"
[1] 4315
[1] TRUE
[1] "0.46"
[1] 4316
[1] TRUE
[1] "0.46"
[1] 4317
[1] TRUE
[1] "1.08"
[1] 4318
[1] TRUE
[1] "1.08"
[1] 4319
[1] TRUE
[1] "0.74"
[1] 4320
[1] TRUE
[1] "0.74"
[1] 4321
[1] TRUE
[1] "7.52"
[1] 4322
[1] TRUE
[1] "7.52"
[1] 4323
[1] TRUE
[1] "0.97"
[1] 4324
[1] TRUE
[1] "0.97"
[1] 4325
[1] TRUE
[1] "0.95"
[1] 4326
[1] TRUE
[1] "0.95"
[1] 4327
[1] TRUE
[1] "1.2"
[1] 4328
[1] TRUE
[1] "0.75"
[1] 4329
[1] TRUE
[1] "0.75"
[1] 4330
[1] TRUE
[1] "0.86"
[1] 4331
[1] TRUE
[1] "1.01"
[1] 4332
[1] TRUE
[1] "1.01"
[1] 4333
[1] TRUE
[1] "12.28"
[1] 4334
[1] TRUE
[1] "1.7"
[1] 4335
[1] TRUE
[1] "1.36"
[1] 4336
[1] TRUE
[1] "1.47"
[1] 4337
[1] TRUE
[1] "1.47"
[1] 4338
[1] TRUE
[1] "0.96"
[1] 4339
[1] TRUE
[1] "0.96"
[1] 4340
[1] TRUE
[1] "1.59"
[1] 4341
[1] TRUE
[1] "0.7"
[1] 4342
[1] TRUE
[1] "0.7"
[1] 4343
[1] TRUE
[1] "2.24"
[1] 4344
[1] TRUE
[1] "2.24"
[1] 4345
[1] TRUE
[1] "1.04"
[1] 4346
[1] TRUE
[1] "1.04"
[1] 4347
[1] TRUE
[1] "1.71"
[1] 4348
[1] TRUE
[1] "1.71"
[1] 4349
[1] TRUE
[1] "2.47"
[1] 4350
[1] TRUE
[1] "2.3"
[1] 4351
[1] TRUE
[1] "2.3"
[1] 4352
[1] TRUE
[1] "0.49"
[1] 4353
[1] TRUE
[1] "0.49"
[1] 4354
[1] TRUE
[1] "1.38"
[1] 4355
[1] TRUE
[1] "1.38"
[1] 4356
[1] TRUE
[1] "7.48"
[1] 4357
[1] TRUE
[1] "4.32"
[1] 4358
[1] TRUE
[1] "4.32"
[1] 4359
[1] TRUE
[1] "4.32"
[1] 4360
[1] TRUE
[1] "8.21"
[1] 4361
[1] TRUE
[1] "8.21"
[1] 4362
[1] TRUE
[1] "8.21"
[1] 4363
[1] TRUE
[1] "0.82"
[1] 4364
[1] TRUE
[1] "0.82"
[1] 4365
[1] TRUE
[1] "0.82"
[1] 4366
[1] TRUE
[1] "8.08"
[1] 4367
[1] TRUE
[1] "8.08"
[1] 4368
[1] TRUE
[1] "8.08"
[1] 4369
[1] TRUE
[1] "2.97"
[1] 4370
[1] TRUE
[1] "2.97"
[1] 4371
[1] TRUE
[1] "2.97"
[1] 4372
[1] TRUE
[1] "4.73"
[1] 4373
[1] TRUE
[1] "4.73"
[1] 4374
[1] TRUE
[1] "2.99"
[1] 4375
[1] TRUE
[1] "2.99"
[1] 4376
[1] TRUE
[1] "5.44"
[1] 4377
[1] TRUE
[1] "5.44"
[1] 4378
[1] TRUE
[1] "5.44"
[1] 4379
[1] TRUE
[1] "1.04"
[1] 4380
[1] TRUE
[1] "1.04"
[1] 4381
[1] TRUE
[1] "10.28"
[1] 4382
[1] TRUE
[1] "10.28"
[1] 4383
[1] TRUE
[1] "10.28"
[1] 4384
[1] TRUE
[1] "0.5"
[1] 4385
[1] TRUE
[1] "0.5"
[1] 4386
[1] TRUE
[1] "0.88"
[1] 4387
[1] TRUE
[1] "0.88"
[1] 4388
[1] TRUE
[1] "0.9"
[1] 4389
[1] TRUE
[1] "0.9"
[1] 4390
[1] TRUE
[1] "0.9"
[1] 4391
[1] TRUE
[1] "6.32"
[1] 4392
[1] TRUE
[1] "6.32"
[1] 4393
[1] TRUE
[1] "17.74"
[1] 4394
[1] TRUE
[1] "17.74"
[1] 4395
[1] TRUE
[1] "17.79"
[1] 4396
[1] TRUE
[1] "17.79"
[1] 4397
[1] TRUE
[1] "17.79"
[1] 4398
[1] TRUE
[1] "0.82"
[1] 4399
[1] TRUE
[1] "0.82"
[1] 4400
[1] TRUE
[1] "1.36"
[1] 4401
[1] TRUE
[1] "1.36"
[1] 4402
[1] TRUE
[1] "2.56"
[1] 4403
[1] TRUE
[1] "2.56"
[1] 4404
[1] TRUE
[1] "2.56"
[1] 4405
[1] TRUE
[1] "10.12"
[1] 4406
[1] TRUE
[1] "10.12"
[1] 4407
[1] TRUE
[1] "10.12"
[1] 4408
[1] TRUE
[1] "8.63"
[1] 4409
[1] TRUE
[1] "8.63"
[1] 4410
[1] TRUE
[1] "1.95"
[1] 4411
[1] TRUE
[1] "1.95"
[1] 4412
[1] TRUE
[1] "1.56"
[1] 4413
[1] TRUE
[1] "1.56"
[1] 4414
[1] TRUE
[1] "1.26"
[1] 4415
[1] TRUE
[1] "1.26"
[1] 4416
[1] TRUE
[1] "1.17"
[1] 4417
[1] TRUE
[1] "1.17"
[1] 4418
[1] TRUE
[1] "8.23"
[1] 4419
[1] TRUE
[1] "8.23"
[1] 4420
[1] TRUE
[1] "19.62"
[1] 4421
[1] TRUE
[1] "19.62"
[1] 4422
[1] TRUE
[1] "8.13"
[1] 4423
[1] TRUE
[1] "8.13"
[1] 4424
[1] TRUE
[1] "13.38"
[1] 4425
[1] TRUE
[1] "13.38"
[1] 4426
[1] TRUE
[1] "4.83"
[1] 4427
[1] TRUE
[1] "4.83"
[1] 4428
[1] TRUE
[1] "5.28"
[1] 4429
[1] TRUE
[1] "5.28"
[1] 4430
[1] TRUE
[1] "3.5"
[1] 4431
[1] TRUE
[1] "3.5"
[1] 4432
[1] TRUE
[1] "4.63"
[1] 4433
[1] TRUE
[1] "4.63"
[1] 4434
[1] TRUE
[1] "17.65"
[1] 4435
[1] TRUE
[1] "17.65"
[1] 4436
[1] TRUE
[1] "6.28"
[1] 4437
[1] TRUE
[1] "6.28"
[1] 4438
[1] TRUE
[1] "2.97"
[1] 4439
[1] TRUE
[1] "2.97"
[1] 4440
[1] TRUE
[1] "2.97"
[1] 4441
[1] TRUE
[1] "0.9"
[1] 4442
[1] TRUE
[1] "0.9"
[1] 4443
[1] TRUE
[1] "8.47"
[1] 4444
[1] TRUE
[1] "8.47"
[1] 4445
[1] TRUE
[1] "1.29"
[1] 4446
[1] TRUE
[1] "1.29"
[1] 4447
[1] TRUE
[1] "1.29"
[1] 4448
[1] TRUE
[1] "0.59"
[1] 4449
[1] TRUE
[1] "0.59"
[1] 4450
[1] TRUE
[1] "0.59"
[1] 4451
[1] TRUE
[1] "3.78"
[1] 4452
[1] TRUE
[1] "3.78"
[1] 4453
[1] TRUE
[1] "7.51"
[1] 4454
[1] TRUE
[1] "7.51"
[1] 4455
[1] TRUE
[1] "3.06"
[1] 4456
[1] TRUE
[1] "3.06"
[1] 4457
[1] TRUE
[1] "6.72"
[1] 4458
[1] TRUE
[1] "6.72"
[1] 4459
[1] TRUE
[1] "6.72"
[1] 4460
[1] TRUE
[1] "1.94"
[1] 4461
[1] TRUE
[1] "1.4"
[1] 4462
[1] TRUE
[1] "2.08"
[1] 4463
[1] TRUE
[1] "0.9"
[1] 4464
[1] TRUE
[1] "0.9"
[1] 4465
[1] TRUE
[1] "2.85"
[1] 4466
[1] TRUE
[1] "2.85"
[1] 4467
[1] TRUE
[1] "5.94"
[1] 4468
[1] TRUE
[1] "5.94"
[1] 4469
[1] TRUE
[1] "5.94"
[1] 4470
[1] TRUE
[1] "5.94"
[1] 4471
[1] TRUE
[1] "7.19"
[1] 4472
[1] TRUE
[1] "7.19"
[1] 4473
[1] TRUE
[1] "13.42"
[1] 4474
[1] TRUE
[1] "13.42"
[1] 4475
[1] TRUE
[1] "13.42"
[1] 4476
[1] TRUE
[1] "13.42"
[1] 4477
[1] TRUE
[1] "12.35"
[1] 4478
[1] TRUE
[1] "12.35"
[1] 4479
[1] TRUE
[1] "7.67"
[1] 4480
[1] TRUE
[1] "7.67"
[1] 4481
[1] TRUE
[1] "7.67"
[1] 4482
[1] TRUE
[1] "7.67"
[1] 4483
[1] TRUE
[1] "8.23"
[1] 4484
[1] TRUE
[1] "8.23"
[1] 4485
[1] TRUE
[1] "6.18"
[1] 4486
[1] TRUE
[1] "6.18"
[1] 4487
[1] TRUE
[1] "6.18"
[1] 4488
[1] TRUE
[1] "6.18"
[1] 4489
[1] TRUE
[1] "7.38"
[1] 4490
[1] TRUE
[1] "7.38"
[1] 4491
[1] TRUE
[1] "1.3"
[1] 4492
[1] TRUE
[1] "1.55"
[1] 4493
[1] TRUE
[1] "1.55"
[1] 4494
[1] TRUE
[1] "4.3"
[1] 4495
[1] TRUE
[1] "4.3"
[1] 4496
[1] TRUE
[1] "7.17"
[1] 4497
[1] TRUE
[1] "7.17"
[1] 4498
[1] TRUE
[1] "5.02"
[1] 4499
[1] TRUE
[1] "5.02"
[1] 4500
[1] TRUE
[1] "1.7"
[1] 4501
[1] TRUE
[1] "1.7"
[1] 4502
[1] TRUE
[1] "1.7"
[1] 4503
[1] TRUE
[1] "1.7"
[1] 4504
[1] TRUE
[1] "2.65"
[1] 4505
[1] TRUE
[1] "2.65"
[1] 4506
[1] TRUE
[1] "5.87"
[1] 4507
[1] TRUE
[1] "5.87"
[1] 4508
[1] TRUE
[1] "4.21"
[1] 4509
[1] TRUE
[1] "4.21"
[1] 4510
[1] TRUE
[1] "5.34"
[1] 4511
[1] TRUE
[1] "0.5"
[1] 4512
[1] TRUE
[1] "21.7"
[1] 4513
[1] TRUE
[1] "3.9"
[1] 4514
[1] TRUE
[1] "100"
[1] 4515
[1] TRUE
[1] "2.3"
[1] 4516
[1] TRUE
[1] "0.4"
[1] 4517
[1] TRUE
[1] "99.6"
[1] 4518
[1] TRUE
[1] "3.2"
[1] 4519
[1] TRUE
[1] "2.6"
[1] 4520
[1] TRUE
[1] "13.6"
[1] 4521
[1] TRUE
[1] "24.1"
[1] 4522
[1] TRUE
[1] "100"
[1] 4523
[1] TRUE
[1] "100"
[1] 4524
[1] TRUE
[1] "2.92"
[1] 4525
[1] TRUE
[1] "2.92"
[1] 4526
[1] TRUE
[1] "2.92"
[1] 4527
[1] TRUE
[1] "2.92"
[1] 4528
[1] TRUE
[1] "5.57"
[1] 4529
[1] TRUE
[1] "5.57"
[1] 4530
[1] TRUE
[1] "5.57"
[1] 4531
[1] TRUE
[1] "5.57"
[1] 4532
[1] TRUE
[1] "7.28"
[1] 4533
[1] TRUE
[1] "7.28"
[1] 4534
[1] TRUE
[1] "7.28"
[1] 4535
[1] TRUE
[1] "7.28"
[1] 4536
[1] TRUE
[1] "3.67"
[1] 4537
[1] TRUE
[1] "3.67"
[1] 4538
[1] TRUE
[1] "3.67"
[1] 4539
[1] TRUE
[1] "3.67"
[1] 4540
[1] TRUE
[1] "11.73"
[1] 4541
[1] TRUE
[1] "11.73"
[1] 4542
[1] TRUE
[1] "11.73"
[1] 4543
[1] TRUE
[1] "11.73"
[1] 4544
[1] TRUE
[1] "99.32"
[1] 4545
[1] TRUE
[1] "5.76"
[1] 4546
[1] TRUE
[1] "5.76"
[1] 4547
[1] TRUE
[1] "25.08"
[1] 4548
[1] TRUE
[1] "7.26"
[1] 4549
[1] TRUE
[1] "7.26"
[1] 4550
[1] TRUE
[1] "2.84"
[1] 4551
[1] TRUE
[1] "2.84"
[1] 4552
[1] TRUE
[1] "2.84"
[1] 4553
[1] TRUE
[1] "2.84"
[1] 4554
[1] TRUE
[1] "10.17"
[1] 4555
[1] TRUE
[1] "8.26"
[1] 4556
[1] TRUE
[1] "8.26"
[1] 4557
[1] TRUE
[1] "2.73"
[1] 4558
[1] TRUE
[1] "2.73"
[1] 4559
[1] TRUE
[1] "1.88"
[1] 4560
[1] TRUE
[1] "14.65"
[1] 4561
[1] TRUE
[1] "0.3"
[1] 4562
[1] TRUE
[1] "1.4"
[1] 4563
[1] TRUE
[1] "1.4"
[1] 4564
[1] TRUE
[1] "0.5"
[1] 4565
[1] TRUE
[1] "4.8"
[1] 4566
[1] TRUE
[1] "1.9"
[1] 4567
[1] TRUE
[1] "1.9"
[1] 4568
[1] TRUE
[1] "1.9"
[1] 4569
[1] TRUE
[1] "1.9"
[1] 4570
[1] TRUE
[1] "2.3"
[1] 4571
[1] TRUE
[1] "2.3"
[1] 4572
[1] TRUE
[1] "2.7"
[1] 4573
[1] TRUE
[1] "2.7"
[1] 4574
[1] TRUE
[1] "2.3"
[1] 4575
[1] TRUE
[1] "2.3"
[1] 4576
[1] TRUE
[1] "9.7"
[1] 4577
[1] TRUE
[1] "9.7"
[1] 4578
[1] TRUE
[1] "9.7"
[1] 4579
[1] TRUE
[1] "4.4"
[1] 4580
[1] TRUE
[1] "4.4"
[1] 4581
[1] TRUE
[1] "4.4"
[1] 4582
[1] TRUE
[1] "4.4"
[1] 4583
[1] TRUE
[1] "4.4"
[1] 4584
[1] TRUE
[1] "4.4"
[1] 4585
[1] TRUE
[1] "5.3"
[1] 4586
[1] TRUE
[1] "5.3"
[1] 4587
[1] TRUE
[1] "5.3"
[1] 4588
[1] TRUE
[1] "6.4"
[1] 4589
[1] TRUE
[1] "6.4"
[1] 4590
[1] TRUE
[1] "6.4"
[1] 4591
[1] TRUE
[1] "5.3"
[1] 4592
[1] TRUE
[1] "5.3"
[1] 4593
[1] TRUE
[1] "5.3"
[1] 4594
[1] TRUE
[1] "0.6"
[1] 4595
[1] TRUE
[1] "0.6"
[1] 4596
[1] TRUE
[1] "0.6"
[1] 4597
[1] TRUE
[1] "0.6"
[1] 4598
[1] TRUE
[1] "0.8"
[1] 4599
[1] TRUE
[1] "0.8"
[1] 4600
[1] TRUE
[1] "0.8"
[1] 4601
[1] TRUE
[1] "0.8"
[1] 4602
[1] TRUE
[1] "0.8"
[1] 4603
[1] TRUE
[1] "0.8"
[1] 4604
[1] TRUE
[1] "5.4"
[1] 4605
[1] TRUE
[1] "5.4"
[1] 4606
[1] TRUE
[1] "5.4"
[1] 4607
[1] TRUE
[1] "5.4"
[1] 4608
[1] TRUE
[1] "5.4"
[1] 4609
[1] TRUE
[1] "5.4"
[1] 4610
[1] TRUE
[1] "7.7"
[1] 4611
[1] TRUE
[1] "7.7"
[1] 4612
[1] TRUE
[1] "7.7"
[1] 4613
[1] TRUE
[1] "5"
[1] 4614
[1] TRUE
[1] "5"
[1] 4615
[1] TRUE
[1] "5"
[1] 4616
[1] TRUE
[1] "4.7"
[1] 4617
[1] TRUE
[1] "4.7"
[1] 4618
[1] TRUE
[1] "4.7"
[1] 4619
[1] TRUE
[1] "0.9"
[1] 4620
[1] TRUE
[1] "0.9"
[1] 4621
[1] TRUE
[1] "0.9"
[1] 4622
[1] TRUE
[1] "0.9"
[1] 4623
[1] TRUE
[1] "0.9"
[1] 4624
[1] TRUE
[1] "0.9"
[1] 4625
[1] TRUE
[1] "1"
[1] 4626
[1] TRUE
[1] "1"
[1] 4627
[1] TRUE
[1] "1"
[1] 4628
[1] TRUE
[1] "1.2"
[1] 4629
[1] TRUE
[1] "1.2"
[1] 4630
[1] TRUE
[1] "1.2"
[1] 4631
[1] TRUE
[1] "1"
[1] 4632
[1] TRUE
[1] "1"
[1] 4633
[1] TRUE
[1] "1"
[1] 4634
[1] TRUE
[1] "1.2"
[1] 4635
[1] TRUE
[1] "1.2"
[1] 4636
[1] TRUE
[1] "1.2"
[1] 4637
[1] TRUE
[1] "1.2"
[1] 4638
[1] TRUE
[1] "1.4"
[1] 4639
[1] TRUE
[1] "1.4"
[1] 4640
[1] TRUE
[1] "1.7"
[1] 4641
[1] TRUE
[1] "1.7"
[1] 4642
[1] TRUE
[1] "1.4"
[1] 4643
[1] TRUE
[1] "1.4"
[1] 4644
[1] "5.2"
[1] 4645
[1] "5.2"
[1] 4646
[1] "5.2"
[1] 4647
[1] "5.2"
[1] 4648
[1] "6.3"
[1] 4649
[1] "6.3"
[1] 4650
[1] "4.4"
[1] 4651
[1] "4.4"
[1] 4652
[1] "4.9"
[1] 4653
[1] "4.9"
[1] 4654
[1] TRUE
[1] "3.8"
[1] 4655
[1] TRUE
[1] "3.8"
[1] 4656
[1] TRUE
[1] "3.8"
[1] 4657
[1] TRUE
[1] "3.8"
[1] 4658
[1] TRUE
[1] "4.6"
[1] 4659
[1] TRUE
[1] "4.6"
[1] 4660
[1] TRUE
[1] "5.5"
[1] 4661
[1] TRUE
[1] "5.5"
[1] 4662
[1] TRUE
[1] "4.6"
[1] 4663
[1] TRUE
[1] "4.6"
[1] 4664
[1] TRUE
[1] "1.3"
[1] 4665
[1] TRUE
[1] "1.3"
[1] 4666
[1] TRUE
[1] "1.5"
[1] 4667
[1] TRUE
[1] "1.5"
[1] 4668
[1] TRUE
[1] "4.6"
[1] 4669
[1] TRUE
[1] "4.6"
[1] 4670
[1] TRUE
[1] "4.6"
[1] 4671
[1] TRUE
[1] "4.6"
[1] 4672
[1] TRUE
[1] "4.6"
[1] 4673
[1] TRUE
[1] "4.6"
[1] 4674
[1] TRUE
[1] "6.6"
[1] 4675
[1] TRUE
[1] "6.6"
[1] 4676
[1] TRUE
[1] "6.6"
[1] 4677
[1] TRUE
[1] "5.8"
[1] 4678
[1] TRUE
[1] "5.8"
[1] 4679
[1] TRUE
[1] "5.8"
[1] 4680
[1] TRUE
[1] "6.6"
[1] 4681
[1] TRUE
[1] "6.6"
[1] 4682
[1] TRUE
[1] "6.6"
[1] 4683
[1] TRUE
[1] "6.3"
[1] 4684
[1] TRUE
[1] "6.3"
[1] 4685
[1] TRUE
[1] "6.3"
[1] 4686
[1] "1.3"
[1] 4687
[1] "1.3"
[1] 4688
[1] "1.3"
[1] 4689
[1] "1.3"
[1] 4690
[1] "1.3"
[1] 4691
[1] "1.3"
[1] 4692
[1] "1.6"
[1] 4693
[1] "1.6"
[1] 4694
[1] "1.6"
[1] 4695
[1] "1.9"
[1] 4696
[1] "1.9"
[1] 4697
[1] "1.9"
[1] 4698
[1] "1.6"
[1] 4699
[1] "1.6"
[1] 4700
[1] "1.6"
[1] 4701
[1] TRUE
[1] "5.5"
[1] 4702
[1] TRUE
[1] "5.5"
[1] 4703
[1] TRUE
[1] "6.6"
[1] 4704
[1] TRUE
[1] "6.6"
[1] 4705
[1] TRUE
[1] "5.5"
[1] 4706
[1] TRUE
[1] "5.5"
[1] 4707
[1] TRUE
[1] "1.3"
[1] 4708
[1] TRUE
[1] "1.3"
[1] 4709
[1] TRUE
[1] "1.3"
[1] 4710
[1] TRUE
[1] "1.3"
[1] 4711
[1] TRUE
[1] "1.6"
[1] 4712
[1] TRUE
[1] "1.6"
[1] 4713
[1] TRUE
[1] "1.9"
[1] 4714
[1] TRUE
[1] "1.9"
[1] 4715
[1] TRUE
[1] "1.6"
[1] 4716
[1] TRUE
[1] "1.6"
[1] 4717
[1] "1.3"
[1] 4718
[1] "1.3"
[1] 4719
[1] "1.3"
[1] 4720
[1] "1.3"
[1] 4721
[1] "1.6"
[1] 4722
[1] "1.6"
[1] 4723
[1] "1.9"
[1] 4724
[1] "1.9"
[1] 4725
[1] "1.6"
[1] 4726
[1] "1.6"
[1] 4727
[1] TRUE
[1] "3.5"
[1] 4728
[1] TRUE
[1] "3.5"
[1] 4729
[1] TRUE
[1] "3.5"
[1] 4730
[1] TRUE
[1] "3.5"
[1] 4731
[1] TRUE
[1] "4.2"
[1] 4732
[1] TRUE
[1] "4.2"
[1] 4733
[1] TRUE
[1] "5.1"
[1] 4734
[1] TRUE
[1] "5.1"
[1] 4735
[1] TRUE
[1] "4.2"
[1] 4736
[1] TRUE
[1] "4.2"
[1] 4737
[1] TRUE
[1] "1.2"
[1] 4738
[1] TRUE
[1] "1.2"
[1] 4739
[1] TRUE
[1] "1.2"
[1] 4740
[1] TRUE
[1] "1.2"
[1] 4741
[1] TRUE
[1] "1.4"
[1] 4742
[1] TRUE
[1] "1.4"
[1] 4743
[1] TRUE
[1] "1.7"
[1] 4744
[1] TRUE
[1] "1.7"
[1] 4745
[1] TRUE
[1] "1.4"
[1] 4746
[1] TRUE
[1] "1.4"
[1] 4747
[1] TRUE
[1] "15.5"
[1] 4748
[1] TRUE
[1] "15.5"
[1] 4749
[1] TRUE
[1] "15.5"
[1] 4750
[1] TRUE
[1] "3"
[1] 4751
[1] TRUE
[1] "3"
[1] 4752
[1] TRUE
[1] "3"
[1] 4753
[1] TRUE
[1] "3"
[1] 4754
[1] TRUE
[1] "3"
[1] 4755
[1] TRUE
[1] "3"
[1] 4756
[1] TRUE
[1] "3.6"
[1] 4757
[1] TRUE
[1] "3.6"
[1] 4758
[1] TRUE
[1] "3.6"
[1] 4759
[1] TRUE
[1] "4.4"
[1] 4760
[1] TRUE
[1] "4.4"
[1] 4761
[1] TRUE
[1] "4.4"
[1] 4762
[1] TRUE
[1] "3.6"
[1] 4763
[1] TRUE
[1] "3.6"
[1] 4764
[1] TRUE
[1] "3.6"
[1] 4765
[1] TRUE
[1] "0.4"
[1] 4766
[1] TRUE
[1] "0.4"
[1] 4767
[1] "1.1"
[1] 4768
[1] "1.1"
[1] 4769
[1] "1.1"
[1] 4770
[1] "1.1"
[1] 4771
[1] "1.6"
[1] 4772
[1] "1.6"
[1] 4773
[1] "1.3"
[1] 4774
[1] "1.3"
[1] 4775
[1] TRUE
[1] "4.2"
[1] 4776
[1] TRUE
[1] "1.4"
[1] 4777
[1] TRUE
[1] "1.4"
[1] 4778
[1] TRUE
[1] "1.7"
[1] 4779
[1] TRUE
[1] "1.7"
[1] 4780
[1] TRUE
[1] "0.9"
[1] 4781
[1] TRUE
[1] "0.9"
[1] 4782
[1] TRUE
[1] "1"
[1] 4783
[1] TRUE
[1] "1"
[1] 4784
[1] "1.5"
[1] 4785
[1] "1.5"
[1] 4786
[1] "1.5"
[1] 4787
[1] "1.5"
[1] 4788
[1] "1.7"
[1] 4789
[1] "1.7"
[1] 4790
[1] "1.9"
[1] 4791
[1] "1.9"
[1] 4792
[1] "1.7"
[1] 4793
[1] "1.7"
[1] 4794
[1] TRUE
[1] "2.2"
[1] 4795
[1] TRUE
[1] "2.2"
[1] 4796
[1] TRUE
[1] "2.2"
[1] 4797
[1] TRUE
[1] "9.4"
[1] 4798
[1] TRUE
[1] "9.4"
[1] 4799
[1] TRUE
[1] "9.4"
[1] 4800
[1] TRUE
[1] "2.6"
[1] 4801
[1] TRUE
[1] "2.6"
[1] 4802
[1] TRUE
[1] "2.6"
[1] 4803
[1] TRUE
[1] "2.6"
[1] 4804
[1] TRUE
[1] "2.6"
[1] 4805
[1] TRUE
[1] "2.6"
[1] 4806
[1] TRUE
[1] "3.3"
[1] 4807
[1] TRUE
[1] "3.3"
[1] 4808
[1] TRUE
[1] "3.3"
[1] 4809
[1] TRUE
[1] "3.5"
[1] 4810
[1] TRUE
[1] "3.5"
[1] 4811
[1] TRUE
[1] "3.5"
[1] 4812
[1] TRUE
[1] "3.3"
[1] 4813
[1] TRUE
[1] "3.3"
[1] 4814
[1] TRUE
[1] "3.3"
[1] 4815
[1] TRUE
[1] "1.2"
[1] 4816
[1] TRUE
[1] "1.2"
[1] 4817
[1] TRUE
[1] "2.1"
[1] 4818
[1] TRUE
[1] "2.1"
[1] 4819
[1] TRUE
[1] "2.1"
[1] 4820
[1] TRUE
[1] "2.1"
[1] 4821
[1] TRUE
[1] "3"
[1] 4822
[1] TRUE
[1] "3"
[1] 4823
[1] TRUE
[1] "2.5"
[1] 4824
[1] TRUE
[1] "2.5"Step 5: Visual and statistical quality checks
Visualisation was performed in the harmonised data library for nutrient evaluation and missing values identification.
Including:
- Identification of data gaps & errors. Systematically non-reported fishery products and/or food components.
- Identification of missing values. For example, fishery products and food components were reported but high number of missing values were found.
- Outliers. Values were extremely low or high compared within the same ICS SUA fishery category.
Step 6: Data formatting & exporting
Food component values were calculated for each ICS SUA fishery category.
Mean or re-calculation of food components were computed & evaluated.
Fishery data library was exported to excel.
The Extended Fisheries Global NCT (2022)
Fishery products per FCTs
Food composition data for fishery products: Overview (1)
4824* fish and fishery products were compiled from 12 FCTs.
9 FCTs were open and freely accessible and cleaned for all foods.
30 food components were reported from more than 100 compiled variables.
Harmonisation of the data
Tagname re-naming was needed in all FCTs,
- 4 FCTs did not report Tagnames (DK19, NZ18, BA13 & NO21)
“Lower quality values” were reported in 4 FCTs (JA15, KE18, WA19 & UF16).
Trace and/or below limit of detection values were transformed to zero in 6 FCTs (IN17 (“<LOD”), BA13, BR11, JA15 (“Tr”), KE18 & WA19 (“tr”)).
Measurement units transformation was needed for Tryptophan,Vitamin A, DHA and EPA in 3 FCTs (US19, IN17 & JA15).
Fisheries categories matching in Norwegian FCT (2021)
ISSCAAP code was allocated to 79% (183/232) of the fish items in NO21, of which
- 89% (n=164) of the matches which were using the scientific names
- 10% (n=19) were done manually using scientific name/ food description.
95 ICS SUA fishery categories were matched to 234* fish and fishery products for use in the NCT.
Data Availability
Data Availability
Data Availability
Data Availability
Transformation & Harmonisation
7 food components (SOP, Energy (kcal, kJ), Carbohydrates by difference, Vitamin A (RAE, RE) and Beta-Carotene Eq.) were re-calculated.
4 food components (Ash, Beta-Carotene Eq., Retinol, and Niacin) were back-calculated.
3 nutrients each (Fat, Thiamine and Vitamin B6) had multiple variables which were integrated.
Evaluating 10 nutrients based on data availability
Figure 1: Availability of data: Percentage (%) of fish entries with values of selected components.
Checking for ICS SUA category data gaps
| Fish categories | Data available (count) per fish category and nutrient | |||||||
|---|---|---|---|---|---|---|---|---|
| Water | Vitamin B6 | Vitamin B12 | Selenium | Niacin | DHA | EPA | Copper | |
| Aquatic animals nei, cured | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 |
| Aquatic animals nei, fresh | 8 | 8 | 8 | 5 | 8 | 5 | 5 | 5 |
| Aquatic animals nei, preparations nei | 2 | 2 | 2 | 0 | 2 | 2 | 2 | 2 |
| Aquatic mammals, meat | 15 | 4 | 4 | 4 | 7 | 4 | 4 | 7 |
| Aquatic mammals, oils | 5 | 2 | 3 | 3 | 5 | 3 | 3 | 3 |
| Aquatic mammals, preparations nei | 5 | 3 | 3 | 2 | 4 | 3 | 3 | 3 |
| Aquatic plants | 9 | 9 | 9 | 9 | 9 | 8 | 8 | 9 |
| Aquatic plants, dried | 24 | 24 | 24 | 12 | 24 | 8 | 18 | 24 |
| Aquatic plants, preparations nei | 10 | 9 | 9 | 5 | 10 | 4 | 5 | 10 |
| Cephalopods, canned | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |
| Cephalopods, cured | 4 | 4 | 4 | 0 | 4 | 4 | 4 | 4 |
| Cephalopods, fresh | 32 | 32 | 27 | 27 | 32 | 24 | 24 | 30 |
| Cephalopods, frozen | 33 | 33 | 28 | 28 | 33 | 25 | 25 | 31 |
| Cephalopods, preparations nei | 41 | 41 | 41 | 38 | 41 | 26 | 26 | 39 |
| Crustaceans, canned | 7 | 7 | 7 | 5 | 7 | 5 | 5 | 7 |
| Crustaceans, cured | 2 | 2 | 2 | 0 | 2 | 1 | 1 | 2 |
| Crustaceans, fresh | 88 | 80 | 69 | 70 | 81 | 45 | 42 | 87 |
| Crustaceans, frozen | 89 | 81 | 70 | 71 | 82 | 46 | 43 | 88 |
| Crustaceans, preparations nei | 116 | 114 | 114 | 100 | 116 | 59 | 53 | 113 |
| Demersal fish, body oils | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Demersal fish, canned | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 3 |
| Demersal fish, cured | 13 | 12 | 12 | 11 | 13 | 10 | 10 | 11 |
| Demersal fish, fresh | 154 | 152 | 107 | 108 | 154 | 146 | 146 | 153 |
| Demersal fish, fresh fillets | 86 | 85 | 85 | 81 | 86 | 57 | 57 | 85 |
| Demersal fish, frozen, fillets | 89 | 88 | 88 | 84 | 89 | 59 | 59 | 88 |
| Demersal fish, frozen, whole | 155 | 153 | 108 | 109 | 155 | 146 | 146 | 154 |
| Demersal fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Demersal fish, preparations nei | 248 | 242 | 235 | 204 | 248 | 177 | 178 | 240 |
| Diadromous fish, body oils | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Diadromous fish, canned | 20 | 19 | 20 | 18 | 19 | 15 | 15 | 20 |
| Diadromous fish, cured | 21 | 20 | 20 | 19 | 20 | 17 | 17 | 20 |
| Diadromous fish, fresh | 60 | 56 | 53 | 47 | 59 | 52 | 52 | 56 |
| Diadromous fish, fresh fillets | 32 | 32 | 30 | 30 | 32 | 14 | 13 | 32 |
| Diadromous fish, frozen fillets | 32 | 32 | 30 | 30 | 32 | 14 | 13 | 32 |
| Diadromous fish, frozen, whole | 60 | 56 | 53 | 47 | 59 | 52 | 52 | 56 |
| Diadromous fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Diadromous fish, preparations nei | 116 | 110 | 111 | 96 | 116 | 70 | 70 | 110 |
| Freshwater & diadromous fish, body oils | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Freshwater & diadromous fish, canned | 21 | 20 | 21 | 19 | 20 | 16 | 16 | 21 |
| Freshwater & diadromous fish, cured | 25 | 24 | 24 | 23 | 24 | 21 | 21 | 24 |
| Freshwater & diadromous fish, fresh | 127 | 122 | 83 | 78 | 125 | 88 | 88 | 123 |
| Freshwater & diadromous fish, fresh fillets | 79 | 75 | 64 | 56 | 79 | 32 | 29 | 75 |
| Freshwater & diadromous fish, frozen fillets | 85 | 81 | 68 | 60 | 85 | 36 | 33 | 81 |
| Freshwater & diadromous fish, frozen, whole | 129 | 124 | 83 | 78 | 127 | 88 | 88 | 125 |
| Freshwater & diadromous fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Freshwater & diadromous fish, preparations nei | 241 | 228 | 231 | 185 | 241 | 144 | 138 | 227 |
| Freshwater fish, body oils | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Freshwater fish, canned | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Freshwater fish, cured | 21 | 20 | 20 | 19 | 20 | 17 | 17 | 20 |
| Freshwater fish, fresh | 60 | 59 | 23 | 24 | 59 | 29 | 29 | 60 |
| Freshwater fish, fresh fillets | 47 | 43 | 34 | 26 | 47 | 18 | 16 | 43 |
| Freshwater fish, frozen fillets | 52 | 48 | 37 | 29 | 52 | 21 | 19 | 48 |
| Freshwater fish, frozen, whole | 62 | 61 | 23 | 24 | 61 | 29 | 29 | 62 |
| Freshwater fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Freshwater fish, preparations nei | 114 | 107 | 109 | 79 | 114 | 63 | 57 | 107 |
| Marine fish nei, preparations nei | 294 | 282 | 279 | 207 | 294 | 183 | 184 | 278 |
| Marine fish nei, body oils | 4 | 4 | 4 | 4 | 4 | 3 | 3 | 4 |
| Marine fish nei, canned | 67 | 66 | 65 | 40 | 67 | 51 | 51 | 65 |
| Marine fish nei, cured | 26 | 25 | 25 | 12 | 26 | 23 | 23 | 24 |
| Marine fish nei, fresh | 153 | 147 | 148 | 84 | 153 | 131 | 131 | 148 |
| Marine fish nei, fresh fillets | 136 | 135 | 133 | 119 | 136 | 87 | 84 | 135 |
| Marine fish nei, frozen fillets | 139 | 138 | 136 | 122 | 139 | 89 | 86 | 138 |
| Marine fish nei, frozen, whole | 154 | 148 | 149 | 85 | 154 | 131 | 131 | 149 |
| Marine fish nei, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Molluscs, excluding cephalopods, canned | 9 | 9 | 9 | 5 | 9 | 8 | 8 | 9 |
| Molluscs, excluding cephalopods, cured | 8 | 8 | 8 | 6 | 8 | 8 | 8 | 8 |
| Molluscs, excluding cephalopods, fresh | 82 | 82 | 77 | 63 | 82 | 49 | 49 | 82 |
| Molluscs, excluding cephalopods, frozen | 81 | 81 | 76 | 62 | 81 | 48 | 48 | 81 |
| Other pelagic fish, body oils | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Other pelagic fish, canned | 30 | 30 | 29 | 20 | 30 | 23 | 23 | 30 |
| Other pelagic fish, cured | 2 | 2 | 2 | 1 | 2 | 2 | 2 | 2 |
| Other pelagic fish, fresh | 29 | 28 | 21 | 22 | 29 | 23 | 23 | 27 |
| Other pelagic fish, fresh fillets | 21 | 21 | 19 | 14 | 21 | 14 | 13 | 21 |
| Other pelagic fish, frozen fillets | 21 | 21 | 19 | 14 | 21 | 14 | 13 | 21 |
| Other pelagic fish, frozen, whole | 29 | 28 | 21 | 22 | 29 | 23 | 23 | 27 |
| Other pelagic fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Other pelagic fish, preparations nei | 22 | 19 | 22 | 11 | 22 | 11 | 11 | 19 |
| Pelagic fish, body oils | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Pelagic fish, canned | 75 | 74 | 73 | 48 | 75 | 60 | 60 | 73 |
| Pelagic fish, cured | 22 | 22 | 22 | 10 | 22 | 22 | 22 | 21 |
| Pelagic fish, fresh | 98 | 94 | 64 | 75 | 98 | 83 | 83 | 94 |
| Pelagic fish, fresh fillets | 50 | 50 | 48 | 38 | 50 | 31 | 28 | 50 |
| Pelagic fish, frozen fillets | 50 | 50 | 48 | 38 | 50 | 31 | 28 | 50 |
| Pelagic fish, frozen, whole | 98 | 94 | 64 | 75 | 98 | 83 | 83 | 94 |
| Pelagic fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Pelagic fish, preparations nei | 103 | 97 | 101 | 60 | 103 | 63 | 63 | 95 |
| Small pelagic fish, body oils | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Small pelagic fish, canned | 35 | 34 | 34 | 18 | 35 | 27 | 27 | 33 |
| Small pelagic fish, cured | 15 | 15 | 15 | 4 | 15 | 15 | 15 | 15 |
| Small pelagic fish, fresh | 61 | 58 | 35 | 46 | 61 | 53 | 53 | 59 |
| Small pelagic fish, fresh fillets | 30 | 30 | 30 | 25 | 30 | 17 | 15 | 30 |
| Small pelagic fish, frozen fillets | 30 | 30 | 30 | 25 | 30 | 17 | 15 | 30 |
| Small pelagic fish, frozen, whole | 61 | 58 | 35 | 46 | 61 | 53 | 53 | 59 |
| Small pelagic fish, liver oils | 6 | 5 | 5 | 5 | 6 | 2 | 2 | 5 |
| Small pelagic fish, preparations nei | 72 | 69 | 70 | 40 | 72 | 43 | 43 | 67 |
Selenium imputation and documentation (1)
- The only missing data were selenium (Se) in four ICS SUA categories
- Imputation was performed and documented in R(studio) (
missing.R). - Documentation can be found in
commentvariable in the Fisheries Global NCT.
Selenium imputation and documentation (2)
| food_desc | SEmcg | source_fct | comment |
|---|---|---|---|
| Crustacean, Sakura shrimp, dried | 101.69 | JA15 | SEmcg value from water adjusted value JA15 (10325)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Mollusks, firefly squid, seasoned and smoked | 131.19 | JA15 | SEmcg value from water adjusted, median values JA15(10342, 10345)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Mollusks, processed squid, "Surume" dried squid | 135.96 | JA15 | SEmcg value from water adjusted, median values JA15(10342, 10345) | CARTBEQmcg_std calculated from CARTBmcg, CARTAmcg and CRYPXBmcg |
| Mollusks, processed squid, "Saki-ika" dried, seasoned and shredded squid | 125.39 | JA15 | SEmcg value from water adjusted, median values JA15(10342, 10345)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Mollusks, processed squid, seasoned and smoked | 96.26 | JA15 | SEmcg value from water adjusted, median values JA15(10342, 10345)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Sea urchin, "Tsubu-uni" salted whole gonads | 228.64 | JA15 | SEmcg value from water adjusted value JA15(10372)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Sea urchin, "Neri-uni" salted whole gonad paste | 222.47 | JA15 | SEmcg value from water adjusted value JA15(10372)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Jellyfish, Salted, desalted | 27.51 | JA15 | CHOAVLDFg_std assumed zero,SEmcg value from water adjusted value JA15(10372) | CARTBEQmcg_std calculated from CARTBmcg, CARTAmcg and CRYPXBmcg |
| Sea cucumber, "Konowata" salted and fermented viscera | 93.92 | JA15 | SEmcg value from water adjusted value JA15(10372)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Sea squirt, "Shiokara" salted and fermented meat and viscera [Syn. Ascidian] | 96.29 | JA15 | SEmcg value from water adjusted value JA15(10372)| CARTBEQmcg_std imputed with CARTBEQmcg |
| Shrimp (crayfish), whole, dried | 153.20 | WA19 | SEmcg value from water adjusted, median values UF16(092001, 092002, 092003, 092004) | CARTBEQmcg_std calculated from CARTBmcg, CARTAmcg and CRYPXBmcg |
Missing values for Fatty Acids (DHA and EPA) by ICS SUA Fishery Category
Missing values for Fatty Acids (DHA and EPA) by ICS SUA Fishery Category
Visualisation for decision making: outliers
Checking outliers: Copper
| source_fct | fdc_id | food_desc | WATERg | CUmg |
|---|---|---|---|---|
| JA15 | 10350 | Mollusks, firefly squid, seasoned and smoked | 23.00 | 12.00 |
| UF16 | 093013 | European flat oyster, flesh, raw | 85.20 | 7.50 |
| IN17 | R003 | Octopus | 80.45 | 6.72 |
| US19 | 11667 | Seaweed, spirulina, dried | 4.68 | 6.1 |
| US19 | 15170 | Mollusks, oyster, eastern, canned | 85.14 | 4.461 |
| NZ18 | T8 | Oyster, Pacific, flesh, raw | 79.70 | 4.21 |
| JA15 | 10371 | Crustacean, mantis shrimp, boiled | 77.20 | 3.46 |
| JA15 | 10348 | Mollusks, firefly squid, raw | 83.00 | 3.42 |
| IN17 | Q006 | Oyster | 82.50 | 3.41 |
| JA15 | 10325 | Crustacean, Sakura shrimp, dried | 19.40 | 3.34 |
| JA15 | 10291 | Mollusks, Escargot Apple snails, canned in brine | 79.90 | 3.07 |
| JA15 | 10349 | Mollusks, firefly squid, boiled | 78.10 | 2.97 |
| JA15 | 10360 | Mollusks, ocellated octopus, raw | 83.20 | 2.96 |
| UF16 | 093011 | American cupped oyster, flesh, wild, raw (USA) | 87.85 | 2.8580000000000001 |
| US19 | 15167 | Mollusks, oyster, eastern, wild, raw | 89.04 | 2.858 |
| IN17 | S003 | Freshwater Eel | 75.57 | 2.72 |
Other visual & quality checks: Water
subset(fao_fish_fct,
str_detect(food_desc, " dry| dried")&
!str_detect(food_desc, "stewed|cooked")&
WATERg>30,
select = c(source_fct, food_desc, WATERg)) %>%
distinct()| source_fct | food_desc | WATERg |
|---|---|---|
| JA15 | Fish, Japanese sand lance, "Niboshi" boiled and dried whole | 38.00 |
| JA15 | Fish, righteye flounder, dried | 74.60 |
| JA15 | Fish, Pacific herring, "Migaki-nishin" dried fillet | 60.60 |
| JA15 | Fish, Pacific herring, "Hirakiboshi" dried split | 59.80 |
| NO21 | Salmon fillet, dry salted, with sugar and spices | 61.00 |
| US19 | Walrus, meat, dried (Alaska Native) | 38.80 |
| US19 | Seal, bearded (Oogruk), meat, dried, in oil (Alaska Native) | 35.48 |
Other visual & quality checks: Sum of Proximate
Other visual & quality checks: Carbohydrates by difference
Documentation
A document with all the decisions and assumptions was generated.
In the NCT,
commentswere added as a separated column with all the data transformations: imputation, assumed zero, calculated, etc.Scripts are provided to fully reproduce the approach and/or to update if needed.
The advantages of a scripted approach
Thomas Codd
The advantages of a scripted approach
- Changes to the data are recorded in the script, not just in the data itself
- Repeatable results (given the same input data and scripts have been run)
- Easy to reapply processes after new data is integrated to the dataset
- Produces a framework to solve a problem or produce a certain output, which can then be modified
How a scripted approach allows for fast updates (1)
An update can come in a number of forms:
- Type 1: The data itself is updated, but the data format and structure remains the same
- Type 2: The data is updated and the dataset is expanded (e.g. new columns added)
- Type 3: The data is updated and/or expanded, and the data format or structure is altered
How a scripted approach allows for fast updates (2)
- Type 1 solution: No change
- Type 2 solution: Modify input script to account for new fields (renaming and reformatting etc)
- Type 3 solution: Recreate input script to account for new data format
How a scripted approach allows for fast updates - the function aspect
- Code segments of similar function can be repurposed for specific use-cases
- Code segments can be written with express intent to complete a function with the least amount of adaptation required - functions
- Several functions were written throughout this project, and tens of thousands of line of adaptable code
How a scripted approach allows for re-use of the FCT for new purposes through data interoperability
- Once an FCT has been processed into an interoperable format the data can be re-used very easily, in R and out
- Within R interoperable datasets can be combined with each other, subsetted, analysed, or adapted for other projects very easily
- Exporting data to a csv and .xlsx document for use in other software is also easy to do
Reuse through interoperability - Example
Reuse through interoperability - Example
Documentation, and Collaborative Reproducibility with Git, GitHub & Sharepoint
Liberty Mlambo
Documentation, and Collaborative Reproducibility with Git, GitHub & Sharepoint
Fully reproducible data & documentation is provided within the repository available at https://github.com/LuciaSegovia/FAO-fisheries
A report covering: data curation steps, variable description, reference to external resources used, and describing any assumptions and challenges.(Available also in pdf)
All these steps would allow to replicate the process and to re-generate the table with the same format for future updates.
Conclusion & Recommendations for the future
What has been completed?
Expanded & updated the Fisheries Global NCT:
- 21 + 6 additional food components for 95 ICS SUA Fisheries Categories.
- Additional components were compiled but not reported.
- 12 FCTs harmonised into a FCT data library.
A framework to reproduce and update FCTs and NCTs:
- Re-usable scripts and functions.
- Reproducible workflow & report.
An opportunity
- For 12 FCTs all data was imported & harmonised in R(Studio).
- The scripts from this project could be re-used to create NCTs for other foods.
- “Easily” expanding with new FCTs into the NCT.
What needs to be further advanced?
Assessment of the impact of the assumptions on the final results (including imputation, calculation, assumed zero, and edible portion).
Improving the metadata of the FCTs and NCTs.
Better reporting of the food composition data.
- Including methods of analysis, sampling and locations.
- Avoiding ambiguous and non-standard reporting.
- Transparent provenance of re-used data.
- More analytical data prioritised for key foods and nutrients.
Better data for Nutrition
More food composition analysis are required, particularly for some fishery categories & nutrients.
- “Aquatic Animals nei”, and fish oils in general.
- DHA, EPA & Selenium.
High variability in certain nutrient concentration paired with high uncertainty.
- Low number of values and highly variable.
- Low or uncertain data quality.
- Broad spectrum of fish and fishery products within one ICS SUA Fishery Category.
Improving data quality & reporting
Imputation techniques and their overall impact on mean values should be evaluated.
Food component description and combination of different methods of analysis (i.e., used for Vitamin B6).
Other data management practices and their impact on final results (i.e., using “low quality values”, assuming zero for trace values, data recycling, etc.).
FCT documentation for reproducibility, transparency and efficiency (i.e., minimum information standards, metadata, ontologies).
THANK YOU!
Q&A
